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The Google Walkout for Real Change group tweeted out their protest against the news of ‘Google confirming that it paid $135 million as exit packages to the two top execs accused of sexual assault, on Twitter, earlier this week. The group castigated the ‘multi-million dollar payouts’ and asked people to use the hashtag #GooglePayoutsForAll to demonstrate different and better ways this obscenely large amount of ‘hush money’ could have been used. https://twitter.com/GoogleWalkout/status/1105556617662214145 The news of Google paying its senior execs, namely, Amit Singhal (former Senior VP of Google search) and Andy Rubin (creator of Android) high exit packages was first highlighted in a report by the New York Times, last October. As per the report, Google paid $90 million to Rubin and $15 million to Singhal. A lawsuit filed by James Martin, an Alphabet shareholder, on Monday this week, further confirmed this news. The lawsuit states that this decision taken by directors of Alphabet caused significant financial harm to the company apart from deteriorating its reputation, goodwill, and market capitalization. Meredith Whittaker, one of the early organizers of the Google Walkout in November last month tweeted, “$135 million could fix Flint's water crisis and still have $80 million left.” Vicki Tardif, another Googler summed up the sentiments in her tweet, “$135M is 1.35 times what Google.org  gave out in grants in 2016.” An ACLU researcher pointed out that $135M could have in addition to feeding the hungry, housing the homeless and pay off some student loans, It could also support local journalism killed by online ads. The public support to the call for protest using the hashtag #GooglePayoutsForAll has been awe-inspiring. Some shared their stories of injustice in cases of sexual assault, some condemned Google for its handling of sexual misconduct, while others put the amount of money Google wasted on these execs into a larger perspective. Better ways Google could have used $135 million it wasted on execs payouts, according to Twitter Invest in people to reduce structural inequities in the company $135M could have been paid to the actual victims who faced harassment and sexual assault. https://twitter.com/xzzzxxzx/status/1105681517584572416 Google could have used the money to fix the wage and level gap for women of color within the company. https://twitter.com/sparker2/status/1105511306465992705 $135 million could be used to adjust the 16% median pay gap of the 1240 women working in Google’s UK offices https://twitter.com/crschmidt/status/1105645484104998913 $135M could have been used by Google for TVC benefits. It could also be used to provide rigorous training to the Google employees on what impact misinformation within the company can have on women and other marginalized groups.   https://twitter.com/EricaAmerica/status/1105546835526107136 For $135M, Google could have paid the 114 creators featured in its annual "YouTube Rewind" who are otherwise unpaid for their time and participation. https://twitter.com/crschmidt/status/1105641872033230848 Improve communities by supporting social causes Google could have paid $135M to RAINN, a largest American nonprofit anti-sexual assault organization, covering its expenses for the next 18 years. https://twitter.com/GoogleWalkout/status/1105450565193121792 For funding 1800 school psychologists for 1 year in public schools https://twitter.com/markfickett/status/1105640930936324097 To build real, affordable housing solutions in collaboration with London Breed, SFGOV, and other Bay Area officials https://twitter.com/jillianpuente/status/1105922474930245636 $135M could provide insulin for nearly 10,000 people with Type 1 diabetes in the US https://twitter.com/GoogleWalkout/status/1105585078590210051 To pay for the first year for 1,000 people with stage IV breast cancer https://twitter.com/GoogleWalkout/status/1105845951938347008 Be a responsible corporate citizen To fund approximately 5300 low-cost electric vehicles for Google staff, and saving around 25300 metric tons of carbon dioxide from vehicle emissions per year. https://twitter.com/crschmidt/status/1105698893361233926 Providing free Google Fiber internet to 225,000 homes for a year https://twitter.com/markfickett/status/1105641215389773825 To give $5/hr raise to 12,980 service workers at Silicon Valley tech campuses https://twitter.com/LAuerhahn/status/1105487572069801985 $135M could have been used for the construction of affordable homes, protecting 1,100 low-income families in San Jose from coming rent hikes of Google’s planned mega-campus. https://twitter.com/JRBinSV/status/1105478979543154688 #GooglePayoutsForAll: Another initiative to promote awareness of structural inequities in tech   The core idea behind launching #GooglePayoutsForAll on Twitter by the Google walkout group was to promote awareness among people regarding the real issues within the company. It urged people to discuss how Google is failing at maintaining the ‘open culture’ that it promises to the outside world. It also highlights how mottos such as “Don’t be Evil” and “Do the right thing” that Google stood by only make for pretty wall decor and there’s still a long way to go to see those ideals in action. The group gained its name when more than 20,000 Google employees along with vendors, and contractors, temps, organized Google “walkout for real change” and walked out of their offices in November 2018. The walkout was a protest against the hushed and unfair handling of sexual misconduct within Google. Ever since then, Googlers have been consistently taking initiatives to bring more transparency, accountability, and fairness within the company. For instance, the team launched an industry-wide awareness campaign to fight against forced arbitration in January, where they shared information about arbitration on their Twitter and Instagram accounts throughout the day. The campaign was a success as Google finally ended its forced arbitration policy which goes into effect this month for all the employees (including contractors, temps, vendors) and for all kinds of discrimination. Also, House and Senate members in the US have proposed a bipartisan bill to prohibit companies from using forced arbitration clauses, last month.    Although many found the #GooglePayoutsForAll idea praiseworthy, some believe this initiative doesn’t put any real pressure on Google to bring about a real change within the company. https://twitter.com/Jeffanie16/status/1105541489722081290 https://twitter.com/Jeffanie16/status/1105546783063752709 https://twitter.com/Jeffanie16/status/1105547341862457344 Now, we don’t necessarily disagree with this opinion, however, the initiative can't be completely disregarded as it managed to make people who’d otherwise hesitate to open up talk extensively regarding the real issues within the company. As Liz Fong-Jones puts it, “Strikes and walkouts are more sustainable long-term than letting Google drive each organizer out one by one. But yes, people *are* taking action in addition to speaking up. And speaking up is a bold step in companies where workers haven't spoken up before”. The Google Walkout group have not yet announced what they intend to do next following this digital protest. However, the group has been organizing meetups such as the one earlier this month on March 6th where it invited the tech contract workers for discussion about building solidarity to make work better for everyone. We are only seeing the beginning of a powerful worker movement take shape in Silicon Valley. Recode Decode #GoogleWalkout interview shows why data and evidence don’t always lead to right decisions in even the world’s most data-driven company Liz Fong Jones, prominent ex-Googler shares her experience at Google and ‘grave concerns’ for the company Google’s pay equity analysis finds men, not women, are underpaid; critics call out design flaws in the analysis

According to a complaint filed in a lawsuit yesterday, Google paid $135 million in total as exit packages to top two senior execs, namely Andy Rubin (creator of Android) and Amit Singhal (former senior VP of Google search) after they were accused of sexual misconduct in the company. The lawsuit was filed by an Alphabet shareholder, James Martin, in the Santa Clara, California Court. Google also confirmed paying the exit packages to senior execs to The Verge, yesterday. Speaking of the lawsuit, the complaint is against certain directors and officers of Alphabet, Google’s parent company, for their active and direct participation in “multi-year scheme” to hide sexual harassment and discrimination at Alphabet. It also states that the misconduct by these directors has caused severe financial and reputational damage to Alphabet. The exit packages for Rubin and Singhal were approved by the Leadership Development and Compensation Committee (LLDC). The news of Google paying high exit packages to its top execs first came to light last October, after the New York Times released a report on Google, stating that the firm paid $90 million to Rubin and $15 million to Singhal. Rubin had previously also received an offer for a $150 million stock grant, which he then further use to negotiate the $90 million in severance pay, even though he should have been fired for cause without any pay, states the lawsuit. To protest against the handling of sexual misconduct within Google, more than 20,000 Google employees along with vendors, and contractors, temps, organized Google “walkout for real change” and walked out of their offices in November 2018. Googlers also launched an industry-wide awareness campaign to fight against forced arbitration in January, where they shared information about arbitration on their Twitter and Instagram accounts throughout the day.   Last year in November, Google ended its forced arbitration ( a move that was soon followed by Facebook) for its employees (excluding temps, vendors, etc) and only in the case of sexual harassment. This led to contractors writing an open letter on Medium to Sundar Pichai, CEO, Google, in December, demanding him to address their demands of better conditions and equal benefits for contractors. In response to the Google walkout and the growing public pressure, Google finally decided to end its forced arbitration policy for all employees (including contractors) and for all kinds of discrimination within Google, last month. The changes will go into effect for all the Google employees starting March 21st, 2019. Yesterday, the Google walkout for real change group tweeted condemning the multi-million dollar payouts and has asked people to use the hashtag #Googlepayoutsforall to highlight other better ways that money could have been used. https://twitter.com/GoogleWalkout/status/1105450565193121792 “The conduct of Rubin and other executives was disgusting, illegal, immoral, degrading to women and contrary to every principle that Google claims it abides by”, reads the lawsuit. James Martin also filed a lawsuit against Alphabet’s board members, Larry Page, Sergey Brin, and Eric Schmidt earlier this year in January for covering up the sexual harassment allegations against the former top execs at Google. Martin had sued Alphabet for breaching its fiduciary duty to shareholders, unjust enrichment, abuse of power, and corporate waste. “The directors’ wrongful conduct allowed illegal conduct to proliferate and continue. As such, members of the Alphabet’s board were knowing direct enables of sexual harassment and discrimination”, reads the lawsuit. It also states that the board members not only violated the California and federal law but it also violated the ethical standards and guidelines set by Alphabet. Public reaction to the news is largely negative with people condemning Google’s handling of sexual misconduct: https://twitter.com/awesome/status/1105295877487263744 https://twitter.com/justkelly_ok/status/1105456081663225856 https://twitter.com/justkelly_ok/status/1105457965790707713 https://twitter.com/conradwt/status/1105386882135875584 https://twitter.com/mer__edith/status/1105464808831361025 For more information, check out the official lawsuit here. Recode Decode #GoogleWalkout interview shows why data and evidence don’t always lead to right decisions in even the world’s most data-driven company Liz Fong Jones, prominent ex-Googler shares her experience at Google and ‘grave concerns’ for the company Google’s pay equity analysis finds men, not women, are underpaid; critics call out design flaws in the analysis

The two-days long TensorFlow Dev Summit 2019 just got over, leaving in its wake major updates being made to the TensorFlow ecosystem.  The major announcement included the release of the first alpha version of most coveted release TensorFlow 2.0. Also announced were, TensorFlow Lite 1.0, TensorFlow Federated, TensorFlow Privacy and more. TensorFlow Federated In a medium blog post, Alex Ingerman (Product Manager) and Krzys Ostrowski (Research Scientist) introduced the TensorFlow Federated framework on the first day. This open source framework is useful for experimenting with machine learning and other computations on decentralized data. As the name suggests, this framework uses Federated Learning, a learning approach introduced by Google in 2017. This technique enables ML models to collaboratively learn a shared prediction model while keeping all the training data on the device. Thus eliminating machine learning from the need to store the data in the cloud. The authors note that TFF is based on their experiences with developing federated learning technology at Google. TFF uses the Federated Learning API to express an ML model architecture, and then train it across data provided by multiple developers, while keeping each developer’s data separate and local. It also uses the Federated Core (FC) API, a set of lower-level primitives, which enables the expression of a broad range of computations over a decentralized dataset. The authors conclude, “With TFF, we are excited to put a flexible, open framework for locally simulating decentralized computations into the hands of all TensorFlow users. You can try out TFF in your browser, with just a few clicks, by walking through the tutorials.” TensorFlow 2.0.0- alpha0 The event also the release of the first alpha version of the TensorFlow 2.0 framework which came with fewer APIs. First introduced last year in August by Martin Wicke, engineer at Google, TensorFlow 2.0, is expected to come with: Easy model building with Keras and eager execution. Robust model deployment in production on any platform. Powerful experimentation for research. API simplification by reducing duplication removing deprecated endpoints. The first teaser,  TensorFlow 2.0.0- alpha0 version comes with the following changes: API clean-up included removing tf.app, tf.flags, and tf.logging in favor of absl-py. No more global variables with helper methods like tf.global_variables_initializer and tf.get_global_step. Functions, not sessions (tf.Session and session.run -> tf.function). Added support for TensorFlow Lite in TensorFlow 2.0. tf.contrib has been deprecated, and functionality has been either migrated to the core TensorFlow API, to tensorflow/addons, or removed entirely. Checkpoint breakage for RNNs and for Optimizers. Minor bug fixes have also been made to the Keras and Python API and tf.estimator. Read the full list of bug fixes in the changelog. TensorFlow Lite 1.0 The TF-Lite framework is basically designed to aid developers in deploying machine learning and artificial intelligence models on mobile and IoT devices. Lite was first introduced at the I/O developer conference in May 2017 and in developer preview later that year. At the TensorFlow Dev Summit, the team announced a new version of this framework, the TensorFlow Lite 1.0. According to a post by VentureBeat, improvements include selective registration and quantization during and after training for faster, smaller models. The team behind TF-Lite 1.0 says that quantization has helped them achieve up to 4 times compression of some models. TensorFlow Privacy Another interesting library released at the TensorFlow dev summit was TensorFlow Privacy. This Python-based open source library aids developers to train their machine-learning models with strong privacy guarantees. To achieve this, it takes inspiration from the principles of differential privacy. This technique offers strong mathematical guarantees that models do not learn or remember the details about any specific user when training the user data. TensorFlow Privacy includes implementations of TensorFlow optimizers for training machine learning models with differential privacy. For more information, you can go through the technical whitepaper describing its privacy mechanisms in more detail. The creators also note that “no expertise in privacy or its underlying mathematics should be required for using TensorFlow Privacy. Those using standard TensorFlow mechanisms should not have to change their model architectures, training procedures, or processes.” TensorFlow Replicator TF Replicator also released at the TensorFlow Dev Summit, is a software library that helps researchers deploy their TensorFlow models on GPUs and Cloud TPUs. To do this, the creators assure that developers would require minimal effort and need not have previous experience with distributed systems. For multi-GPU computation, TF-Replicator relies on an “in-graph replication” pattern, where the computation for each device is replicated in the same TensorFlow graph. When TF-Replicator builds an in-graph replicated computation, it first builds the computation for each device independently and leaves placeholders where cross-device computation has been specified by the user. Once the sub-graphs for all devices have been built, TF-Replicator connects them by replacing the placeholders with actual cross-device computation. For a more comprehensive description, you can go through the research paper. These were the top announcements made at the TensorFlow Dev Summit 2019. You can go through the Keynote and other videos of the announcements and tutorials on this YouTube playlist. TensorFlow 2.0 to be released soon with eager execution, removal of redundant APIs, tffunction and more. TensorFlow 2.0 is coming. Here’s what we can expect. Google introduces and open-sources Lingvo, a scalable TensorFlow framework for Sequence-to-Sequence Modeling

In this article, we will provide 3 tips for making an interactive conversational application using current chat and voice examples. This is an excerpt from the book Voicebot and Chatbot Design written by Rachel Batish. In this book, the author shares her insights into cutting-edge voice-bot and chatbot technologies Help your users ask the right questions Although this sounds obvious, it is actually crucial to the success of your chatbot or voice-bot. I learned this when I initially set up my Amazon Echo device at home. Using a complementary mobile app, I was directed to ask Alexa specific questions, to which she had good answers to, such as “Alexa, what is the time?” or “Alexa, what is the weather today?” I immediately received correct answers and therefore wasn’t discouraged by a default response saying, “Sorry, I don’t have an answer to that question.” By providing the user with successful experience, we are encouraging them to trust the system and to understand that, although it has its limitations, it is really good in some specific details. Obviously, this isn’t enough because as time passes, Alexa (and Google) continues to evolve and continues to expand its support and capabilities, both internally and by leveraging third parties. To solve this discovery problem, some solutions, like Amazon Alexa and Google Home, send a weekly newsletter with the highlights of their latest capabilities. In the email below, Amazon Alexa is providing a list of questions that I should ask Alexa in my next interaction with it, exposing me to new functionalities like donation. From the Amazon Alexa weekly emails “What’s new with Alexa?” On the Google Home/Assistant, Google has also chosen topics that it recommends its users to interact with. Here, as well, the end user is exposed to new offerings/capabilities/knowledge bases, that may give them the trust needed to ask similar questions on other topics. From the Google Home newsletter Other chat and voice providers can also take advantage of this email communication idea to encourage their users to further interact with their chatbots or voice-bots and expose them to new capabilities. The simplest way of encouraging usage is by adding a dynamic ‘welcoming’ message to the chat voice applications, that includes new features that are enabled. Capital One, for example, updates this information every now and then, exposing its users to new functionalities. On Alexa, it sounds like this: “Welcome to Capital One. You can ask me for things like account balance and recent transactions.” Another way to do this – especially if you are reaching out to a random group of people – is to initiate discovery during the interaction with the user (I call this contextual discovery). For example, a banking chatbot offers information on account balances. Imagine that the user asks, “What’s my account balance?” The system gives its response: “Your checking account balance is $5,000 USD.” The bank has recently activated the option to transfer money between accounts. To expose this information to its users, it leverages the bot to prompt a rational suggestion to the user and say, “Did you know you can now transfer money between accounts? Would you like me to transfer $1,000 to your savings account?” As you can see, the discovery process was done in context with the user’s actions. Not only does the user know that he/she can now transfer money between two accounts, but they can also experience it immediately, within the relevant context. To sum up tip #1, by finding the direct path to initial success, your users will be encouraged to further explore and discover your automated solutions and will not fall back to other channels. The challenge is, of course, to continuously expose users to new functionalities, made available on your chatbots and voice-bots, preferably in a contextual manner. Give your bot a ‘personality’, but don’t pretend it’s a human Your bot, just like any digital solution you provide today, should have a personality that makes sense for your brand. It can be visual, but it can also be enabled over voice. Whether it is a character you use for your brand or something created for your bot, personality is more than just the bot’s icon. It’s the language that it ‘speaks’, the type of interaction that it has and the environment it creates. In any case, don’t try to pretend that your bot is a human talking with your clients. People tend to ask the bot questions like “are you a bot?” and sometimes even try to make it fail by asking questions that are not related to the conversation (like asking how much 30*4,000 is or what the bot thinks of *a specific event*). Let your users know that it’s a bot that they are talking to and that it’s here to help. This way, the user has no incentive to intentionally trip up the bot. ICS.ai have created many custom bots for some of the leading UK public sector organisations like county councils, local governments and healthcare trusts. Their conversational AI chat bots are custom designed by name, appearance and language according to customer needs. Chatbot examples Below are a few examples of chatbots with matching personalities. Expand your vocabulary with a word a day (Wordsworth) The Wordsworth bot has a personality of an owl (something clever), which fits very well with the purpose of the bot: to enrich the user’s vocabulary. However, we can see that this bot has more than just an owl as its ‘presenter’, pay attention to the language and word games and even the joke at the end. Jokes are a great way to deliver personality. From these two screenshots only, we can easily capture a specific image of this bot, what it represents and what it’s here to do. DIY-Crafts-Handmade FB Messenger bot The DIY-Crafts-Handmade bot has a different personality, which signals something light and fun. The language used is much more conversational (and less didactic) and there’s a lot of usage of icons and emojis. It’s clear that this bot was created for girls/women and offers the end user a close ‘friend’ to help them maximize the time they spend at home with the kids or just start some DIY projects. Voicebot examples One of the limitations around today’s voice-enabled devices is the voice itself. Whereas Google and Siri do offer a couple of voices to choose from, Alexa is limited to only one voice and it’s very difficult to create that personality that we are looking for. While this problem probably will be solved in the future, as technology improves, I find insurance company GEICO’s creativity around that very inspiring. In its effort to keep Gecko’s unique voice and personality, GEICO has incorporated multiple MP3 files with a recording of Gecko’s personalized voice. https://www.youtube.com/watch?v=11qo9a1lgBE GEICO has been investing for years in Gecko’s personalization. Gecko is very familiar from TV and radio advertisements, so when a customer activates the Alexa app or Google Action, they know they are in the right place. To make this successful, GEICO incorporated Gecko’s voice into various (non-dynamic) messages and greetings. It also handled the transition back to the device’s generic voice very nicely; after Gecko has greeted the user and provided information on what they can do, it hands it back to Alexa with every question from the user by saying, “My friend here can help you with that.” This is a great example of a cross-channel brand personality that comes to life also on automated solutions such as chatbots and voice-bots. Build an omnichannel solution – find your tool Think less on the design side and more on the strategic side, remember that new devices are not replacing old devices; they are only adding to the big basket of channels that you must support. Users today are looking for different services anywhere and anytime. Providing a similar level of service on all the different channels is not an easy task, but it will play a big part in the success of your application. There are different reasons for this. For instance, you might see a spike in requests coming from home devices such as Amazon Echo and Google Home during the early morning and late at night. However, during the day you will receive more activities from FB Messenger or your intelligent assistant. Different age groups also consume products from different channels and, of course, geography impacts as well. Providing cross-channel/omnichannel support doesn’t mean providing different experiences or capabilities. However, it does mean that you need to make that extra effort to identify the added value of each solution, in order to provide a premium, or at least the most advanced, experience on each channel. Building an omnichannel solution for voice and chat Obviously, there are differences between a chatbot and a voice-bot interaction; we talk differently to how we write and we can express ourselves with emojis while transferring our feelings with voice is still impossible. There are even differences between various voice-enabled devices, like Amazon Alexa and Google Assistant/Home and, of course, Apple’s HomePod. There are technical differences but also behavioral ones. The HomePod offers a set of limited use cases that businesses can connect with, whereas Amazon Alexa and Google Home let us create our own use cases freely. In fact, there are differences between various Amazon Echo devices, like the Alexa Show that offers a complimentary screen and the Echo Dot that lacks in screen and sound in comparison. There are some developer tools today that offer multi-channel integration to some devices and channels. They are highly recommended from a short and long-term perspective. Those platforms let bot designers and bot builders focus on the business logic and structure of their bots, while all the integration efforts are taken care of automatically. Some of those platforms focus on chat and some of them on voice. A few tools offer a bridge between all the automated channels or devices. Among those platforms, you can find Conversation.one (disclaimer: I’m one of the founders), Dexter and Jovo. With all that in mind, it is clear that developing a good conversational application is not an easy task. Developers must prove profound knowledge of machine learning, voice recognition, and natural language processing. In addition to that, it requires highly sophisticated and rare skills, that are extremely dynamic and flexible. In such a high-risk environment, where today’s top trends can skyrocket in days or simply be crushed in just a few months, any initial investment can be dicey. To know more trips and tricks to make a successful chatbot or voice-bot, read the book Voicebot and Chatbot Design by Rachel Batish. Creating a chatbot to assist in network operations [Tutorial] Building your first chatbot using Chatfuel with no code [Tutorial] Conversational AI in 2018: An arms race of new products, acquisitions, and more

In theory, stealing cryptocurrency should be impossible. But a mystery has emerged that seems to throw all that into question and even suggests a bigger, much stranger conspiracy. Gerald Cotten, the founder of cryptocurrency exchange QadrigaCX, died in December in India. He was believed to have left $136 million USD worth of crypto-cash in 'cold wallets' on his own laptop, to which only he had access. However, investigators from EY, who have been working on closing QuadrigaCX following Cotten's death, were surprised to find that the wallets were empty. In fact, it's believed crypto-cash had disappeared from them months before Cotten died. A cryptocurrency mystery now involving the FBI The only lead in this mystery is the fact that the EY investigators have found other user accounts that appear to be linked to Gerald Cotten. There's a chance that Cotten used these to trade on his own exchange, but the nature of these exchanges remain a little unclear. To add to the intrigue, Fortune reported yesterday that the FBI are working with Canada's Mounted Police Force to investigate the missing money. This information came from Jesse Powell, CEO of another cryptocurrency company called Kraken. Powell told Fortune that both the FBI and the Mounted Police have been in touch with him about the mystery surrounding QuadrigaCX. Powell has offered a reward of $100,000 to anyone that can locate the missing cryptocurrency funds. So what actually happened to Gerald Cotten and his crypto-cash? The story has many layers of complexity. There are rumors that Cotten faked his own death. For example, Cotten filed a will just 12 days before his death, leaving a significant amount of wealth and assets to his wife. And while sources from the hospital in India where Cotten is believed to have died say he died of cardiac arrest, as Fortune explains, "Cotten’s body was handled by hotel staff after an embalmer refused to receive it" - something which is, at the very least, strange. It should be noted that there is certainly no clear evidence that Cotten faked his own death - only missing pieces that encourage such rumors. A further subplot - that might or night not be useful in cracking this case - emerged late last week when Canada's Globe and Mail reported that QuadrigaCX's co-founder has a history of identity theft and using digital currencies to launder money. Where could the money be? There are, as you might expect, no shortage of theories about where the cash could be. A few days ago, it was suggested that it might be possible to locate Cotten's Ethereum funds - a blog post by James Edwards, who is the editor of cryptocurrency blog zerononcense claimed that Ethereum linked to QuadrigaCX can be found in Bitfinex, Poloniex, and Jesse Powell's Kraken. "It appears that a significant amount of Ethereum (600,000+ ETH) was transferred to these exchanges as a means of ‘storage’ during the years that QuadrigaCX was in operation and offering Ethereum on their exchange," Edwards writes. Edwards is keen for his findings to be the starting point for a clearer line of inquiry, free from speculation and conspiracy. He wrote that he hoped that it would be "a helpful addition to the QuadrigaCX narrative, rather than a conspiratorial piece that speculates on whether the exchange or its owners have been honest."

It’s not always easy to know what to learn next if you’re a programmer. Industry shifts can be subtle but they can sometimes be dramatic, making it incredibly important to stay on top of what’s happening both in your field and beyond. No one person can make that decision for you. All the thought leadership and mentorship in the world isn’t going to be able to tell you what’s right for you when it comes to your career. But this list of videos, released last month, might give you a helping hand as to where to go next when it comes to your learning… New data science and artificial intelligence video courses for March Apache Spark is carving out a big presence as the go-to software for big data. Two videos from February focus on Spark - Distributed Deep Learning with Apache Spark and Apache Spark in 7 Days. If you’re new to Spark and want a crash course on the tool, then clearly, our video aims to get you up and running quickly. However, Distributed Deep Learning with Apache Spark offers a deeper exploration that shows you how to develop end to end deep learning pipelines that can leverage the full potential of cutting edge deep learning techniques. While we’re on the subject of machine learning, other choice video courses for March include TensorFlow 2.0 New Features (we’ve been eagerly awaiting it and it finally looks like we can see what it will be like), Hands On Machine Learning with JavaScript (yes, you can now do machine learning in the browser), and a handful of interesting videos on artificial intelligence and finance: AI for Finance Machine Learning for Algorithmic Trading Bots with Python Hands on Python for Finance Elsewhere, a number of data visualization video courses prove that communicating and presenting data remains an urgent challenge for those in the data space. Tableau remains one of the definitive tools - you can learn the latest version with Tableau 2019.1 for Data Scientists and Data Visualization Recipes with Python and Matplotlib 3.   New app and web development video courses for March 2019 There are a wealth of video courses for web and app developers to choose from this month. True, Hands-on Machine Learning for JavaScript is well worth a look, but moving past the machine learning hype, there are a number of video courses that take a practical look at popular tools and new approaches to app and web development. Angular’s death has been greatly exaggerated - it remains a pillar of the JavaScript world. While the project’s versioning has arguably been lacking some clarity, if you want to get up to speed with where the framework is today, try Angular 7: A Practical Guide. It’s a video that does exactly what it says on the proverbial tin - it shows off Angular 7 and demonstrates how to start using it in web projects. We’ve also been seeing some uptake of Angular by ASP.NET developers, as it offers a nice complement to the Microsoft framework on the front end side. Our latest video on the combination, Hands-on Web Development with ASP.NET Core and Angular, is another practical look at an effective and increasingly popular approach to full-stack development. Other picks for March include Building Mobile Apps with Ionic 4, a video that brings you right up to date with the recent update that launched in January (interestingly, the project is now backed by web components, not Angular), and a couple of Redux videos - Mastering Redux and Redux Recipes. Redux is still relatively new. Essentially, it’s a JavaScript library that helps you manage application state - because it can be used with a range of different frameworks and libraries, including both Angular and React, it’s likely to go from strength to strength in 2019. Infrastructure, admin and security video courses for March 2019 Node.js is becoming an important library for infrastructure and DevOps engineers. As we move to a cloud native world, it’s a great tool for developing lightweight and modular services. That’s why we’re picking Learn Serverless App Development with Node.js and Azure Functions as one of our top videos for this month. Azure has been growing at a rapid rate over the last 12 months, and while it’s still some way behind AWS, Microsoft’s focus on developer experience is making Azure an increasingly popular platform with developers. For Node developers, this video is a great place to begin - it’s also useful for anyone who simply wants to find out what serverless development actually feels like. Read next: Serverless computing wars: AWS Lambda vs. Azure Functions A partner to this, for anyone beginning Node, is the new Node.js Design Patterns video. In particular, if Node.js is an important tool in your architecture, following design patterns is a robust method of ensuring reliability and resilience. Elsewhere, we have Modern DevOps in Practice, cutting through the consultancy-speak to give you useful and applicable guidance on how to use DevOps thinking in your workflows and processes, and DevOps with Azure, another video that again demonstrates just how impressive Azure is. For those not Azure-inclined, there’s AWS Certified Developer Associate - A Practical Guide, a video that takes you through everything you need to know to pass the AWS Developer Associate exam. There’s also a completely cloud-agnostic video course in the form of Creating a Continuous Deployment Pipeline for Cloud Platforms that’s essential for infrastructure and operations engineers getting to grips with cloud native development.     Learn a new programming language with these new video courses for March Finally, there are a number of new video courses that can help you get to grips with a new programming language. So, perfect if you’ve been putting off your new year’s resolution to learn a new language… Java 11 in 7 Days is a new video that brings you bang up to date with everything in the latest version of Java, while Hands-on Functional Programming with Java will help you rethink and reevaluate the way you use Java. Together, the two videos are a great way for Java developers to kick start their learning and update their skill set.  

In a paper published on February 4, Google engineers drafted out plans to forward federated learning at a scale. It showcases the high-level plans, challenges, solutions, and applications. Federated learning was first introduced in 2017 by Google. The idea is to use data from a number of computing devices like smartphones instead of a centralized data source. Federated learning can help with privacy Federated learning can be beneficial as it addresses the privacy concern. Android phones are used for the system where the data is only used but never uploaded to any server. A deep neural network is trained by using TensorFlow on the data stored in the Android phone. The Federated averaging algorithm by Brendan McMahan uses a similar approach as synchronous training. The weights of the neural network are combined in the cloud using Federated Averaging. This creates a global model which is then pushed back to the phones as results/desirable actions. To enhance privacy approaches like differential privacy and Secure aggregation are taken. The paper addresses challenges like time zone differences, connectivity issues, interrupted execution etc,. Their work is mature enough to deploy the system in production for tens of millions of devices. They are working towards supporting billions of devices now. The training protocol The system involves devices and the Federated Learning server communicating availability and the server selecting devices to run a task. A subset of the available devices are selected for a task. The Federated Learning server instructs the devices what computing task to run with a plan. A plan would consist a TensorFlow graph and instructions to execute it. There are three phases for the training to take place: Selection of the devices that meet eligibility criteria Configuring the server with simple or Secure Aggregation Reporting from the devices where reaching a certain number would get the training round started Source: Towards Federated Learning at Scale: System Design The devices are supposed to maintain a repository of the collected data and the applications are responsible to provide data to the Federated Learning runtime as an example store. The Federated Learning server is designed to operate on orders of many magnitudes. Each round can mean updates from devices in the range of KBs to tens of MBs coming going the server. Data collection To avoid harming the phone’s battery life and performance, various analytics are collected in the cloud. The logs don’t contain any personally identifiable information. Secure aggregation Secure aggregation uses encryption to make individual device updates uninspectable. They plant to use it for protection against threats in data centers. Secure aggregation would ensure data encryption even when it is in-memory. Challenges of federated learning Compared to a centralized dataset, federated learning poses a number of challenges. The training data is not inspectable, tooling is required to work with proxy data. Models cannot be run interactively and must be compiled to be deployed in the Federated Learning server. Model resource consumption and runtime compatibility also come into the picture when working with many devices in real-time. Applications of Federated Learning It is best for cases where the data on devices is more relevant than data on servers. Ranking items for better navigation, suggestions for on-device keyboard, and next word prediction. This has already been implemented on Google pixel and Gboard. Future work is to eliminate bias caused be restrictions in device selection, algorithms to support better parallelism (more devices in one round), avoiding retraining already trained tasks on devices, and compression to save bandwidth. Federated computation, not federated learning The authors do no mention machine learning explicitly anywhere in the paper. They believe that the applications of such a model are not limited to machine learning. Federated Computation is the term they want to use for this concept. Federated computation and edge computing Federated learning and edge computing are very similar, there are but subtle differences in the purpose of these two. Federated learning is used to solve problems with specific tasks assigned to endpoint smartphones. Edge computing is for predefined tasks to be processed at end nodes, for example, IoT cameras. Federated learning decentralizes the data used while edge computing decentralizes the task computation to various devices. For more details on the architecture and its working, you can check out the research paper. Technical and hidden debts in machine learning – Google engineers’ give their perspective Researchers introduce a machine learning model where the learning cannot be proved What if AIs could collaborate using human-like values? DeepMind researchers propose a Hanabi platform.

Kara Swisher, Recode co-founder, interviewed Jack Dorsey, Twitter CEO, yesterday over Twitter. The interview ( or ‘Twitterview’)  was conducted in tweets using the hashtag #KaraJack. It started at 5 pm ET and lasted for around 90-minutes. Let’s have a look at the top highlights from the interview. https://twitter.com/karaswisher/status/1095440667373899776 On Fixing what is broke on Social Media and Physical safety Swisher asked Dorsey why he isn’t moving faster in his efforts to fix the disaster that has been caused so far on social media. To this Dorsey replied that Twitter was trying to do “too much” in the past but that they have become better at prioritizing now. The number one focus for them now is a person’s “physical safety” i.e. the offline ramifications for Twitter users off the platform. “What people do offline with what they see online”, says Dorsey. Some examples of ‘offline ramifications’ being “doxxing” (harassment technique that reveals a person’s personal information on the internet) and coordinated harassment campaigns. Dorsey further added that replies, searches, trends, mentions on Twitter are where most of the abuse happens and are the shared spaces people take advantage of. “We need to put our physical safety above all else. We don’t have all the answers just yet. But that’s the focus. I think it clarifies a lot of the work we need to do. Not all of it of course”, said Dorsey. On Tech responsibility and improving the health of digital conversation on Twitter When Swisher asked Dorsey what grading would he give to Silicon Valley and himself for embodying tech responsibility, he replied with “C” for himself. He said that Twitter has made progress but it’s scattered and ‘not felt enough’. He did not comment on what he thought of Silicon Valley’s work in this area. Swisher further highlighted that the goal of improving Twitter conversations have only remained empty talk so far. She asked Dorsey if Twitter has made any actual progress in the last 18-24 months when it comes to addressing the issues regarding the “health of conversation” (which eventually plays into safety). Dorsey said these issues are the most important thing right now that they need to fix and it’s a failure on Twitter’s part to ‘put the burden on victims’. He did not share a specific example of improvements made to the platform to further this goal. Swisher then questioned him on how he intends on fixing the issue, Dorsey mentioned that: Twitter intends to be more proactive when it comes to enforcing healthy conversations so that reporting/blocking becomes the last resort. He mentioned that Twitter takes actions against all offenders who go against its policies but that the system works reactively to someone who reports it. “If they don’t report, we don’t see it. Doesn’t scale. Hence the need to focus on proactive”, said Dorsey. Since Twitter is constantly evolving its policies to address the ‘current issues’, it's rooting these in fundamental human rights (UN) and is making physical safety the top priority alongside privacy. On lack of diversity https://twitter.com/jack/status/1095459084785004544 Swisher questioned Dorsey on his negligence towards addressing the issues. “I think it is because many of the people who made Twitter never ever felt unsafe,” adds Swisher. Dorsey admits that the “lack of diversity” didn’t help with the empathy of what people (especially women) experience on Twitter every day. He further adds that Twitter should be reflective of the people that it’s trying to serve, which is why they established a trust and safety council to get feedback. Swisher then asks him to provide three concrete examples of what Twitter has done to fix this. Dorsey mentioned that Twitter has: evolved its policies ( eg; misgendering policy). prioritized proactive enforcement by using machine learning to downrank bad actors, meaning, they'll look at the probability of abuse from any one account. This is because if someone else is abusing one account then they’re probably doing the same on other accounts. Given more user control in a product, such as muting of accounts with no profile picture, etc. More focus on coordinated behavior/gaming. On Dorsey’s dual CEO role Swisher asked him why he insists on being the CEO of two publicly traded companies (Twitter and Square Inc.) that both require maximum effort at the same time. Dorsey said that his main focus is on building leadership in both and that it’s not his ambition to be CEO of multiple companies “just for the sake of that”. She further questioned him if he has any plans in mind to hire someone as his “number 2”. Dorsey said it’s better to spread that kind of responsibility across several people as it reduces dependencies and the company gets more options for future leadership. “I’m doing everything I can to help both. Effort doesn’t come down to one person. It’s a team”, he said. On Twitter breaks, Donald Trump and Elon Musk When initially asked about what Dorsey feels about people not feeling good after being for a while on Twitter, he said he feels “terrible” and that it's depressing. https://twitter.com/jack/status/1095457041844334593 “We made something with one intent. The world showed us how it wanted to use it. A lot has been great. A lot has been unexpected. A lot has been negative. We weren’t fast enough to observe, learn, and improve”, said Dorsey. He further added that he does not feel good about how Twitter tends to incentivize outrage, fast takes, short term thinking, echo chambers, and fragmented conversations. Swisher then questioned Dorsey on whether Twitter has ever intended on suspending Donald Trump and if Twitter’s business/engagement would suffer when Trump is no longer the president. Dorsey replied that Twitter is independent of any account or person and that although the number of politics conversations has increased on Twitter, that’s just one experience. He further added that Twitter is ready for 2020 elections and that it has partnered up with government agencies to improve communication around threats. https://twitter.com/jack/status/1095462610462433280 Moreover, on being asked about the most exciting influential on Twitter, Dorsey replied with Elon Musk. He said he likes how Elon is focused on solving existential problems and sharing his thinking openly. On being asked he thought of how Alexandria Ocasio Cortez is using Twitter, he replied that she is ‘mastering the medium’. Although Swisher managed to interview Dorsey over Twitter, the ‘Twitterview’ got quite confusing soon and went out of order. The conversations seemed all over the place and as Kurt Wagner, tech journalist from Recode puts it, “in order to find a permanent thread of the chat, you had to visit one of either Kara or Jack’s pages and continually refresh”. This made for a difficult experience overall and points towards the current flaws within the conversation system on Twitter. Many users tweeted out their opinion regarding the same: https://twitter.com/RTKumaraSwamy/status/1095542363890446336 https://twitter.com/waltmossberg/status/1095454665305739264 https://twitter.com/kayvz/status/1095472789870436352 https://twitter.com/sukienniko/status/1095520835861864448 https://twitter.com/LauraGaviriaH/status/1095641232058011648 Recode Decode #GoogleWalkout interview shows why data and evidence don’t always lead to right decisions in even the world’s most data-driven company Twitter CEO, Jack Dorsey slammed by users after a photo of him holding ‘smash Brahminical patriarchy’ poster went viral Jack Dorsey discusses the rumored ‘edit tweet’ button and tells users to stop caring about followers

A leading fact-checking agency, Snopes, announced last week that it’s terminating its partnership with Facebook and will no longer aid in reducing the spread of misinformation and fake news on the platform. “We are evaluating the ramifications and costs of providing third-party fact-checking services, and we want to determine with certainty that our efforts to aid any particular platform are a net positive for our online community, publication, and staff”, reads the statement by David Mikkelson, CEO, Snopes, and Vinny Green, VP operations, Snopes. Facebook had decided to partner up with 3rd party fact checking firms at the end of 2016, to get help in combating false news on its platform following the 2016 US elections. One such firm to partner up with Facebook was Snopes, who contributed to Facebook for two years. Snopes team mentions that when they contributed to Facebook’s initial fact-checking effort in December 2016, there were no financial benefits (payment offer) involved. However, Facebook did offer a lump $100,000 payment for their work in 2017. Other than that, Green told Poynter that part of the reason why Snopes withdrew its partnership with Facebook is that third-party fact-checking for Facebook didn’t seem practical to the publishers within Snopes. He mentions that fact checkers had to manually enter false news post on Facebook that they flag into the dashboard, which in turn, requires a lot of time and is not possible for a team that has only 16 people. “It doesn’t seem like we’re striving to make third-party fact-checking more practical for publishers — it seems like we’re striving to make it easier for Facebook. The work that fact-checkers are doing doesn’t need to be just for Facebook — we can build things for fact-checkers that benefit the whole web, and that can also help Facebook”, Green told Poynter. Offering Fact-checking services for Facebook has been under a lot of controversy within Snopes, as Guardian recently quoted Brooke Binkowski, Snopes’ former managing editor, and Kim LaCapria, a former fact-checker in a report published in December last year. As per the reports, the former Snopes employees mentioned that Facebook ‘didn’t care’ about the fact-checking firms. “They’ve essentially used us for crisis PR. They’re not taking anything seriously. They are more interested in making themselves look good and passing the buck … They clearly don’t care,” said Binkowski. Regarding the current news, a Facebook spokesperson told Poynter that, despite Snopes’ pulling out of the partnership, Facebook will continue to improve its platform and work with fact-checkers around the world. Another agency, named, Associated Press (AP) is also currently making negotiations over its role as a fact-checking agency on Facebook. AP spokesperson told TechCrunch it’s not doing any fact-checking work for Facebook currently and is in an ongoing discussion with Facebook about opportunities related to doing more important fact-checking work on Facebook. AP doesn’t plan on leaving Facebook but is in talks with the company and hopes to start the fact-checking work soon, as reported by TechCrunch. Snopes team also mentioned that they've not entirely ruled out working with Facebook and are willing to have an open dialogue and discussion with Facebook over its approaches to fighting misinformation. “We will continue to be pioneers in a challenging digital media landscape, forever looking for opportunities to cultivate our publication and increase our impact. Our extremely talented and dedicated staff stands ready for the challenges ahead”, states the Snopes team.This is a test for blockquote This is a test for blockquote This is a test for blockquote This is a test for blockquote This is a test for blockquote This is a test for blockquote This is a test for blockquote This is a test for blockquote This is a test for blockquote This is a test for blockquote Read NextFacebook faces multiple data-protection investigations in Ireland Facebook pays users $20/month to install a ‘Facebook Research’ VPN that spies on their phone and web activities, TechCrunch reports Facebook hires top EEF lawyer and Facebook critic as Whatsapp privacy policy manager

Atlantic Council CEO, Frederick Kempe spoke in the World Economic Forum (WEF) in Davos, Switzerland. He talked about the Cold war between the US and China and why the countries need to co-operate and not compete in the tech arms race, in his presentation Future Frontiers of Technology Control. He began his presentation by posing a question set forth by Former US Foreign National Security Advisor Stephen Hadley, “Can the incumbent US and insurgent China become strategic collaborators and strategic competitors in this tech space at the same time?” Read also: The New AI Cold War Between China and the USA Kempe’s three framing arguments Geopolitical Competition This fusion of tech breakthroughs blurring lines of the physical, digital, and biological space is reaching an inflection point that makes it already clear that they will usher in a revolution that will determine the shape of the global economy. It will also determine which nations and political constructs may assume the commanding heights of global politics in the coming decade. Technological superiority Over the course of history, societies that dominated economic innovation and progress have dominated in international relations — from military superiority to societal progress and prosperity. On balance, technological progress has contributed to higher standards of living in most parts of the world; however, the disproportionate benefit goes to first movers. Commanding Heights The technological arms race for supremacy in the fourth industrial revolution has essentially become a two-horse contest between the United States and China. We are in the early stages of this race, but how it unfolds and is conducted will do much to shape global human relations. The shift in 2018 in US-China relations from a period of strategic engagement to greater strategic competition has also significantly accelerated the Tech arms race. China vs the US: Why China has the edge? It was Vladimir Putin, President of the Russian Federation who said that “The one who becomes the leader in Artificial Intelligence, will rule the world.” In 2017, DeepMind’s AlphaGo defeated a Chinese master in Go, a traditional Chinese game. Following this defeat, China launched an ambitious roadmap, called the next generation AI plan. The goal was to become the Global leader in AI by 2030 in theory, technology, and application. On current trajectories, in the four primary areas of AI over the next 5 years, China will emerge the winner of this new technology race. Kempe also quotes, author of the book, AI superpowers, Kai-fu Lee who argues that harnessing of the power of AI today- the electricity of the 21st century- requires abundant data, hungry entrepreneurs, AI scientists, and an AI friendly policy. He believes that China has the edge in all of these. The current AI has translated from out of the box research, where the US has expertise in, to actual implementation, where China has the edge. Per, Kai-fu Lee China already has the edge in entrepreneurship, data, and government support, and is rapidly catching up to the U.S. in expertise. The world has translated from the age of world-leading expertise (US department) to the age of data, where China wins hands down. Economists call China the Saudi Arabia of Data and with that as the fuel for AI, it has an enormous advantage. The Chinese government without privacy restrictions can gain and use data in a manner that is out of reach of any democracy. Kemper concludes that the nature of this technological arms contest may favor insurgent China rather than the incumbent US. What are the societal implications of this tech cold war He also touched upon the societal implications of AI and the cold war between the US and China. A number of jobs will be lost by 2030. Quoting from Kai-fu Lee’s book, Kempe says that Job displacement caused by artificial intelligence and advanced robotics could possibly displace up to 54 million US workers which comprise 30% of the US labor force. It could also displace up to 100 million Chinese workers which are 12% of the Chinese labor force. What is the way forward with these huge societal implications of a bi-lateral race underway? Kempe sees three possibilities. A sloppy Status Quo A status quo where China and the US will continue to cooperate but increasingly view each other with suspicion. They will manage their rising differences and distrust imperfectly, never bridging them entirely, but also not burning bridges, either between researchers, cooperations, or others. Techno Cold War China and the US turn the global tech contest into more of a zero-sum battle for global domination. They organize themselves in a manner that separates their tech sectors from each other and ultimately divides up the world. Collaborative Future - the one we hope for Nicholas Thompson and Ian Bremmer argued in a wired interview that despite the two countries’ societal difference, the US should wrap China in a tech embrace. The two countries should work together to establish international standards to ensure that the algorithms governing people’s lives and livelihoods are transparent and accountable. They should recognize that while the geopolitics of technological change is significant, even more important will be the challenges AI poses to all societies across the world in terms of job automation and the social disruptions that may come with it. It may sound utopian to expect US and China to cooperate in this manner, but this is what we should hope for. To do otherwise would be self-defeating and at the cost of others in the global community which needs our best thinking to navigate the challenges of the fourth industrial revolution. Kempe concludes his presentation with a quote by Henry Kissinger, Former US Secretary of State and National Security Advisor, “We’re in a position in which the peace and prosperity of the world depend on whether China and the US can find a method to work together, not always in agreement, but to handle our disagreements...This is the key problem of our time.” Note: All images in this article are taken from Frederick Kempe’s presentation. We must change how we think about AI, urge AI founding fathers Does AI deserve to be so Overhyped? Alarming ways governments are using surveillance tech to watch you

Conversational AI is one of the most interesting applications of artificial intelligence in recent years. While the trend isn’t yet ubiquitous in the way that recommendation systems are (perhaps unsurprising), it has been successfully productized by a number of tech giants, in the form of Google Home and Amazon Echo (which is ‘powered by’ Alexa). The conversational AI arms race Arguably, 2018 has seen a bit of an arms race in conversational AI. As well as Google and Amazon, the likes of IBM, Microsoft, and Apple have wanted a piece of the action. Here are some of the new conversational AI tools and products these companies introduced this year: Google Google worked towards enhancing its conversational interface development platform, Dialogflow. In July, at the Google Cloud Next event, it announced several improvements and new capabilities to Dialogflow including Text to Speech via DeepMind's WaveNet and Dialogflow Phone Gateway for telephony integration. It also launched a new product called Contact Center AI that comes with Dialogflow Enterprise Edition and additional capabilities to assist live agents and perform analytics. Google Assistant became better in having a back-and-forth conversation with the help of Continued Conversation, which was unveiled at the Google I/O conference. The assistant became multilingual in August, which means users can speak to it in more than one language at a time, without having to adjust their language settings. Users can enable this multilingual functionality by selecting two of the supported languages. Following the footsteps of Amazon, Google also launched its own smart display named Google Home Hub at the ‘Made by Google’ event held in October. Microsoft Microsoft in 2018 introduced and improved various bot-building tools for developers. In May, at the Build conference, Microsoft announced major updates in their conversational AI tools: Azure Bot Service, Microsoft Cognitive Services Language Understanding, and QnAMaker. To enable intelligent bots to learn from example interactions and handle common small talk, it launched new experimental projects from named Conversation Learner and Personality Chat. At Microsoft Ignite, Bot Framework SDK V4.0 was made generally available. Later in November, Microsoft announced the general availability of the Bot Framework Emulator V4 and Web Chat control. In May, to drive more research and development in its conversational AI products, Microsoft acquired Semantic Machines and established conversational AI center of excellence in Berkeley. In November, the organization's acquisition of Austin-based bot startup XOXCO was a clear indication that it wants to get serious about using artificial intelligence for conversational bots. Producing guidelines on developing ‘responsible’ conversational AI further confirmed Microsoft wants to play a big part in the future evolution of the area. Microsoft were the chosen tech partner by UK based conversational AI startup ICS.ai. The team at ICS are using Azure and LUIS from Microsoft in their public sector AI chatbots, aimed at higher education, healthcare trusts and county councils. Amazon Amazon with the aims to improve Alexa’s capabilities released Alexa Skills Kit (ASK) which consists of APIs, tools, documentation, and code samples using which developers can build new skills for Alexa. In September, it announced a preview of a new design language named Alexa Presentation Language (APL). With APL, developers can build visual skills that include graphics, images, slideshows, and video, and to customize them for different device types. Amazon’s smart speaker Echo Dot saw amazing success with becoming the best seller in smart speaker category on Amazon. At its 2018 hardware event in Seattle, Amazon announced the launch of redesigned Echo Dot and a new addition to Alexa-powered A/V device called Echo Plus. As well as the continuing success of Alexa and the Amazon Echo, Amazon’s decision to launch the Alexa Fellowship at a number of leading academic institutions also highlights that for the biggest companies conversational AI is as much about research and exploration as it is products. Like Microsoft, it appears that Amazon is well aware that conversational AI is an area only in its infancy, still in development - as much as great products, it requires clear thinking and cutting-edge insight to ensure that it develops in a way that is both safe and impactful. What’s next? This huge array of products is a result of advances in deep learning researches. Now conversational AI is not just limited to small tasks like setting an alarm or searching the best restaurant. We can have a back and forth conversation with the conversational agent. But, needless to say, it still needs more work. Conversational agents are yet to meet user expectations related to sensing and responding with emotion. In the coming years, we will see these systems understand and do a good job at generating natural language. They will be able to have reasonably natural conversations with humans in certain domains, grounded in context. Also, the continuous development in IoT will provide AI systems with more context. Apple has introduced Shortcuts for iOS 12 to automate your everyday tasks Microsoft amplifies focus on conversational AI: Acquires XOXCO; shares guide to developing responsible bots Amazon is supporting research into conversational AI with Alexa fellowships

A group of Googlers launched a public awareness social media campaign from 9 AM to 6 PM EST yesterday. The group, called, ‘Googlers for ending forced arbitration’ shared information about arbitration on their Twitter and Instagram accounts throughout the day. https://twitter.com/endforcedarb/status/1084813222505410560 The group tweeted out yesterday, as part of the campaign, that in surveying employees of 30+ tech companies and 10+ common Temp/Contractor suppliers in the industry, none of them could meet the three primary criteria needed for a transparent workplace. The three basic criteria include: optional arbitration policy for all employees and for all forms of discrimination (including contractors/temps), no class action waivers, and no gag rule that keeps arbitration hearings proceedings confidential. The group shared some hard facts about Arbitration and also busted myths regarding the same. Let’s have a look at some of the key highlights from yesterday’s campaign. At least 60 million Americans are forced to use arbitration The group states that the implementation of forced arbitration policy has grown significantly in the past seven years. Over 65% of the companies consisting of 1,000 or more employees, now have mandatory arbitration procedures. Employees don’t have an option to take their employers to court in cases of harassment or discrimination. People of colour and women are often the ones who get affected the most by this practice.           How employers use forced Arbitration Forced arbitration is extremely unfair Arbitration firms that are hired by the companies usually always favour the companies over its employees. This is due to the fear of being rejected the next time by an employer lest the arbitration firm decides to favour the employee. The group states that employees are 1.7 times more likely to win in Federal courts and 2.6 times more likely to win in state courts than in arbitration.   There are no public filings of the complaint details, meaning that the company won’t have anyone to answer to regarding the issues within the organization. The company can also limit its obligation when it comes to disclosing the evidence that you need to prove your case.   Arbitration hearings happen behind closed doors within a company When it comes to arbitration hearings, it's just an employee and their lawyer, other party and their lawyer, along with a panel of one to three arbitrators. Each party gets to pick one arbitrator each, who is also hired by your employers. However, there’s usually only a single arbitrator panel involved as three-arbitrator panel costs five times more than a single arbitrator panel, as per the American Arbitration Association. Forced Arbitration requires employees to sign away their right to class action lawsuits at the start of the employment itself The group states that irrespective of having legal disputes or not, forced arbitration bans employees from coming together as a group in case of arbitration as well as in case of class action lawsuits. Most employers also practice “gag rule” which restricts the employee to even talk about their experience with the arbitration policy. There are certain companies that do give you an option to opt out of forced arbitration using an opt-out form but comes with a time constraint depending on your agreement with that company. For instance, companies such as Twitter, Facebook, and Adecco give their employees a chance to opt out of forced arbitration.                                                  Arbitration opt-out option JAMS and AAA are among the top arbitration organizations used by major tech giants JAMS, Judicial Arbitration and Mediation Services, is a private company that is used by employers like Google, Airbnb, Uber, Tesla, and VMware. JAMS does not publicly disclose the diversity of its arbitrators. Similarly, AAA, America Arbitration Association, is a non-profit organization where usually retired judges or lawyers serve as arbitrators. Arbitrators in AAA have an overall composition of 24% women and minorities. AAA is one of the largest arbitration organizations used by companies such as Facebook, Lyft, Oracle, Samsung, and Two Sigma.   Katherine Stone, a professor from UCLA law school, states that the procedure followed by these arbitration firms don’t allow much discovery. What this means is that these firms don’t usually permit depositions or various kinds of document exchange before the hearing. “So, the worker goes into the hearing...armed with nothing, other than their own individual grievances, their own individual complaints, and their own individual experience. They can’t learn about the experience of others,” says Stone. Female workers and African-American workers are most likely to suffer from forced arbitration 58% female workers and 59% African American workers face mandatory arbitration depending on the workgroups. For instance, in the construction industry, which is a highly male-dominated industry, the imposition of forced arbitration is at the lowest rate. But, in the education and health industries, which has the majority of the female workforce, the imposition rate of forced arbitration is high.                                 Forced Arbitration rate among different workgroups Supreme Court has gradually allowed companies to expand arbitration to employees & consumers The group states that the 1925 Federal Arbitration Act (FAA) had legalized arbitration between shipping companies in cases of settling commercial disputes. The supreme court, however, expanded this practice of arbitration to companies too.                                                   Supreme court decisions Apart from sharing these facts, the group also shed insight on dos and don’t that employees should follow under forced arbitration clauses.                                                      Dos and Dont’s The social media campaign by Googlers for forced arbitration represents an upsurge in the strength and courage among the employees within the tech industry as not just the Google employees but also employees from different tech companies shared their experience regarding forced arbitration. The group had researched academic institutions, labour attorneys, advocacy groups, etc, and the contracts of around 30 major tech companies, as a part of the campaign. To follow all the highlights from the campaign, follow the End Forced Arbitration Twitter account. Shareholders sue Alphabet’s board members for protecting senior execs accused of sexual harassment Recode Decode #GoogleWalkout interview shows why data and evidence don’t always lead to right decisions in even the world’s most data-driven company Tech Workers Coalition volunteers talk unionization and solidarity in Silicon Valley

This Festive and New Year period, Packt Publishing Ltd are commissioning their newest group of authors – you, the everyday expert – in order to help the next generation of developers, coders, and architects. Packt, a global leader in publishing technology and coding eBooks and videos,  are asking the technology community to ‘pay it forward’ by looking back at their career and paying their advice forward to support the next generation of technology leaders via a survey.  The aim is to rewrite the code on career development and find out what everyday life looks like for those in our community. The Pay it Forward eBook that will be created, will provide tips and insights from the tech profession. Rather than giving off the shelf advice on how to better your career, Packt are asking everyday experts – the professionals across the globe who make the industry tick – for the insights and advice they would give from the good and the bad that they have seen. The most insightful and useful responses to the survey will be published by Packt in a new eBook, which will be available for free in early 2019. Some of the questions Pay it Forward will seek answers to, include: What is the biggest myth about working in tech? If you could give one career hack, what would it be? How do you keep on top of new developments and news? What are the common challenges you have seen or experienced in your profession? Who do you most admire and why? What is the best piece of advice you have received that has helped you in your career? What advice would you give to a student wishing to enter your profession? Have you actually broken the internet? We all make mistakes, how do you handle them? What do you love about what you do? People can offer their responses here: http://payitforward.packtpub.com/ Commenting on Pay it Forward, Packt Publishing Ltd CEO and founder Dave Maclean, said, “Over time we all gain knowledge through our experiences. We’ve all failed and learned and found better ways to do things.  As we come into the New Year, we’re reflecting on what we have learned and we’re calling on our community of everyday experts to share their knowledge with people who are new to the industry, to the next generation of changemakers.” “For our part, Packt will produce a book that pulls together this advice and make it available for free to help those wishing to pursue a career within technology.” The survey should take no more than 10 minutes to complete and is in complete confidence, with no disclosure of names or details, unless agreed.

The asinine charade that is CES is running in Las Vegas this week. Describing itself as 'the global stage of innovation', CES attempts to set the agenda for a new year in tech. While ostensibly it's an opportunity to see how technology might impact the lives of all of us over the next decade (or more), it is, in truth, a vapid carnival that does nothing but make the technology industry look stupid. Okay, perhaps I'm being a fun sponge: what's wrong with smart doorbells, internet connected planks of wood and other madcap ideas? Well, nothing really - but those inventions are only the tip of the iceberg. Disagree? Don't worry: you can find the biggest announcements from day one of CES 2019 here. What CES gets wrong Where CES really gets it wrong - and where it drives down a dead end of vacuity - is how it showcases the mind numbing rush to productize and then commercialize some of the really serious developments that could transform the world in a way that is ultimately far less trivial than the glitz and glamor of the way it is presented in the media would suggest. This isn't to say that there there won't be important news and interesting discussions to come out of CES. But even the more interesting topics can be diluted, becoming buzzwords for marketers to latch onto. As Wired remarks on Twitter, "the term AI-powered is used loosely and is almost always a marketing ploy, whether or not a product is impacted by AI." In the same thread, the publication's account also notes that 5G, another big theme for the event, won't be widely available for at least another 12 months. https://twitter.com/WIRED/status/1082294957979910144 Ultimately, what this tells us is that the focus of CES isn't really technology - not in the sense of how we build it and how we should use it. Instead, it is an event dedicated to the ways we can sell it. Perhaps in previous years, the gleeful excitement of CES was nothing but a bit of light as we recover from the holiday period. But this year it's different. 2018 was a year of reckoning in tech, as a range of scandals emerged that underlined the ways in which exciting technological innovation can be misused and deployed against the very people we assume it should be helping. From the Cambridge Analytica scandal to the controversy surrounding Amazon's Rekognition, Google's Project Dragonfly, and Microsoft's relationship with ICE, 2018 was a year that made it clearer than ever that buried somewhere beneath novel and amusing inventions, and better quality television screens are a set of interests that have little interest in making life better for people. The corporate glamor of CES 2019 is just kitsch It's not news that there are certain organisations and institutions that don't have the interests of the majority at heart. But CES 2019 does take on a new complexion in the shadow of all that has happened in 2019. The question 'what's the point of all this' takes on a more serious edge. When you add in the dissent that has come from a growing part of the Silicon Valley workforce, CES 2019 starts to look like an event that, much like many industry leaders, wants to bury the messy and complex reality of building software in favor of marketing buzz. In The Unbearable Lightness of Being, the author Milan Kundera describes kitsch as "the absolute denial of shit." It's following this definition that you can see CES as a kitsch event. This is because the it pushes the decisions and inevitable trade offs that go into developing new technologies and products into the shadows. It doesn't take negative consequences seriously. It's all just 'shit' that should be ignored. This all adds up to a message that seems to be: better doesn't even need to be built. It's here already, no risks, no challenges. Developers don't really feature at CES. That's not necessarily a problem - after all, it's not an event for them, and what developer wants to spend time hearing marketers talk about AI? But if 2018 has taught us anything, it's that a culture of commercialization that refuses to consider consequences other than what can be done in the service of business growth can be immensely damaging. It hurts people, and it might even be hurting democracy. Okay, the way to correct things probably isn't to simply invite more engineers to CES. But by the same token, CES is hardly helping things either. Everything important is happening outside the event Everything important seems to be happening at the periphery of this year's CES, in some instances quite literally outside the building. Apple's ad, for example, might have been a clever piece of branding, but it has captured the attention of the world. Arguably, it's more memorable than much of what's happening inside the event. And although it's possible to be cynical, it does nevertheless raise important questions about a number of companies attitudes to user data. https://twitter.com/NateIngraham/status/1081612316532064257 Another big talking point as this year's event began is who isn't present. Due to the government shutdown a number of officials that were due to attend and speak have had to cancel. This acts as a reminder of the wider context in which CES 2019 is taking place, in which a nativist government looks set on controlling controlling who and how people move across borders. It also highlights how euphemistic the phrase 'consumer technology' really is. TVs and cloud connected toilets might take the headlines, but its government surveillance that will likely have the biggest impact on our lives in the future. Not that any of this seemed to matter to Gary Shapiro, the Chief Executive of the Consumer Technology Association (the organization that puts on CES). Speaking to the BBC, Shapiro said: “It’s embarrassing to be on the world stage with a dominant event in the world of technology, and our federal government... can't be there to host their colleague government executives from around the world.” Shapiro's frustration is understandable from an organizer's perspective. But it also betrays the apparent ethos of CES: what's happening outside doesn't matter. We all deserve better than CES 2019 The new products on show at CES 2019 won't make everything better. There's a chance they will make everything worse. Arguably, the more blindly optimistic we are that they'll make things better, the more likely they are to make things worse. It's only by thinking through complex questions, and taking time to consider the possible consequences of our decision making as developers, product managers, or business people that we can actually be sure that things will get better. This doesn't mean we need to stop getting excited about new inventions and innovations. But things like smart cities and driverless cars pose a whole range of issues that shouldn't be buried in the optimistic schmaltz of events like CES. They need care and attention from policy makers, designers, software engineers, and many others to ensure they are actually going to help to build a better world for people.

The huge advancements of deep learning and artificial intelligence were perhaps the biggest story in tech in 2018. But we wanted to know what the future might hold - luckily, we were able to speak to Packt author Will Ballard about what they see as in store for artificial in 2019 and beyond. Will Ballard is the chief technology officer at GLG, responsible for engineering and IT. He was also responsible for the design and operation of large data centers that helped run site services for customers including Gannett, Hearst Magazines, NFL, NPR, The Washington Post, and Whole Foods. He has held leadership roles in software development at NetSolve (now Cisco), NetSpend, and Works (now Bank of America). Explore Will Ballard's Packt titles here. Packt: What do you think the biggest development in deep learning / AI was in 2018? Will Ballard: I think attention models beginning to take the place of recurrent networks is a pretty impressive breakout on the algorithm side. In Packt’s 2018 Skill Up survey, developers across disciplines and job roles identified machine learning as the thing they were most likely to be learning in the coming year. What do you think of that result? Do you think machine learning is becoming a mandatory multidiscipline skill, and why? Almost all of my engineering teams have an active, or a planned machine learning feature on their roadmap. We’ve been able to get all kinds of engineers with different backgrounds to use machine learning -- it really is just another way to make functions -- probabilistic functions -- but functions. What do you think the most important new deep learning/AI technique to learn in 2019 will be, and why? In 2019 -- I think it is going to be all about PyTorch and TensorFlow 2.0, and learning how to host these on cloud PaaS. The benefits of automated machine learning and metalearning How important do you think automated machine learning and metalearning will be to the practice of developing AI/machine learning in 2019? What benefits do you think they will bring? Even ‘simple’ automation techniques like grid search and running multiple different algorithms on the same data are big wins when mastered. There is almost no telling which model is ‘right’ till you try it, so why not let a cloud of computers iterate through scores of algorithms and models to give you the best available answer? Artificial intelligence and ethics Do you think ethical considerations will become more relevant to developing AI/machine learning algorithms going forwards? If yes, how do you think this will be implemented? I think the ethical issues are important on outcomes, and on how models are used, but aren’t the place of algorithms themselves. If a developer was looking to start working with machine learning/AI, what tools and software would you suggest they learn in 2019? Python and PyTorch.