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Welcome to AI_Distilled. Today, we’ll talk about:

Techwave:

[Sponsored] Grow your career by 10x using AI Strategies in 4 hrs!

Apple Intelligence comes to iPhone, iPad, and Mac starting next month

Replit Agent early access

AI system developed by Google DeepMind that designs novel proteins

Introducing LLaVA V1.5 7B on GroqCloud

Function Calling in Google AI Studio

Awesome AI:

Polymet - Idea to prototype within seconds

ClipAnything - Choppity

fal.ai

Earkick - Your Personal AI Chatbot

Outerbase | The interface for your database

Masterclass:

Voice Trigger System for Siri

Align Meta Llama 3 to human preferences with DPO

An Intuitive Intro to RL

Enhancing LLMs with Structured Outputs and Function Calling

Safely repairing broken builds with ML

HackHub:

Agents for software development

Open-source LLM app development platform

build, manage & run useful autonomous agents

Understand Human Behavior to Align True Needs

Generative models for conditional audio generation

Cheers!

Shreyans Singh

Editor-in-Chief, Packt

💡Recommended Reading: Essential Concepts of Vector Databases

Understand why vector databases are important in modern data management and how to use them effectively.

The course is about 4 hours long and is aimed at people interested in advanced data management techniques.

The course includes hands-on sessions for setting up and using these databases, as well as integrating them with Large Language Models and frameworks like LangChain.

Apple Intelligence comes to iPhone, iPad, and Mac starting next month

Apple announced the launch of "Apple Intelligence," a personal intelligence system integrated with iOS 18, iPadOS 18, and macOS Sequoia, starting in October 2024. This system uses advanced generative models and personal context to enhance everyday tasks, like writing assistance, smarter notifications, and a more flexible Siri. Features like a photo Clean Up tool, transcription in Notes and Phone apps, and AI-powered email prioritization will debut first in the U.S., with expanded language and feature support in the following months.

Replit Agent early access

Replit Agent is an AI tool that helps users create software projects by understanding natural language prompts. Currently in early access for Replit Core and Teams subscribers, it assists in building web-based applications by guiding users through each step, from selecting technologies to deploying the final product. The agent is designed for prototyping and works closely with users to refine and develop their applications.

AI system developed by Google DeepMind that designs novel proteins

AlphaProteo is an AI system developed by Google DeepMind that designs novel proteins to bind to specific target molecules. This technology can accelerate biological research by creating protein binders that aid in drug development, disease understanding, and more. AlphaProteo builds on the success of AlphaFold but goes further by generating new proteins, not just predicting their structures. It has shown high success rates in binding to key targets, such as proteins involved in cancer and viral infections like SARS-CoV-2.

Introducing LLaVA V1.5 7B on GroqCloud

LLaVA v1.5 7B is a new multimodal AI model available on GroqCloud, enabling developers and businesses to create applications that integrate image, audio, and text inputs. Built from a combination of OpenAI’s CLIP and Meta’s Llama 2, LLaVA v1.5 excels in tasks like visual question answering, image captioning, and multimodal dialogue.

Function Calling in Google AI Studio

Google AI Studio now supports function calling, allowing users to easily test the model's capabilities directly in the interface. This new feature makes it more convenient to experiment with the AI without leaving the UI. Google AI Studio offers free fine-tuning.

Polymet - Idea to prototype within seconds

Polymet is an AI-powered tool that helps users quickly turn ideas into prototypes by generating designs and production-ready code in seconds. Users can describe what they need, iterate on the design with their team, and then export the code and designs, which can easily integrate with tools like Figma and existing codebases.

ClipAnything - Choppity

Choppity is an AI-powered video editing tool that allows users to quickly find and clip moments from any video using visual, audio, and sentiment analysis. With its "ClipAnything" feature, users can search for specific parts of a video, such as key events, people, or emotions, without having to manually review hours of footage.

fal.ai

Fal.ai is a generative media platform designed for developers to create and deploy AI-powered applications, particularly focused on text-to-image models. It offers fast, cost-effective inference with models like FLUX.1 and Stable Diffusion, optimized for various creative tasks.

Earkick - Your Personal AI Chatbot

Earkick is an AI-powered mental health app that helps users track and improve their emotional well-being in real time through a personal chatbot named Panda. Earkick tracks mental readiness, mood, and calmness, while providing daily insights, breathing techniques, and guided self-care sessions.

Outerbase | The interface for your database

Outerbase is an AI-powered platform that simplifies working with databases for engineers, researchers, and analysts. It supports SQL and NoSQL databases, allowing users to manage data securely while using AI tools to write queries, fix mistakes, and generate charts and visualizations instantly. Outerbase's table editor, dashboards, and data catalog help users organize, analyze, and share insights efficiently.

Voice Trigger System for Siri

Apple's voice trigger system for Siri includes a first-stage low-power detector to identify potential triggers, and a second-stage, high-precision model to confirm the trigger. It also incorporates speaker identification to ensure the device responds only to its primary user. This sophisticated setup addresses challenges like background noise and phonetically similar words while maintaining power efficiency and privacy.

Align Meta Llama 3 to human preferences with DPO

DPO involves fine-tuning a large language model (LLM) based on feedback from human annotators who rate or rank the model's responses according to desired values, such as helpfulness and honesty. SageMaker Studio provides the computational environment to fine-tune the model using Jupyter notebooks with powerful GPU instances, while SageMaker Ground Truth simplifies the process of gathering human feedback by managing workflows for data annotation. Together, they allow you to align the Llama 3 model’s responses with specific organizational values efficiently.

An Intuitive Intro to RL

Reinforcement learning (RL) is a type of machine learning where an agent learns by interacting with its environment, making decisions, and receiving feedback in the form of rewards or penalties. The goal is to maximize cumulative rewards over time. The agent starts with little to no knowledge and improves through trial and error, learning from past experiences. In RL, actions taken by the agent change the state of the environment, and based on the rewards received, the agent adjusts its future actions. A key concept in RL is balancing exploration (trying new things) and exploitation (using known strategies for rewards).

Enhancing LLMs with Structured Outputs and Function Calling

Enhancing LLMs with structured outputs and function calling improves their ability to provide accurate and useful responses. Structured outputs ensure consistency and clarity by organizing information in a logical format, reducing ambiguity. Function calling allows LLMs to perform specific tasks, such as retrieving real-time data or executing external functions, making them more interactive and versatile. Combined with techniques like Retrieval-Augmented Generation (RAG), which integrates relevant external information into the model’s responses, these enhancements lead to more reliable, accurate, and contextually rich conversations with LLMs.

Safely repairing broken builds with ML

Google's engineers have developed a machine learning model called DIDACT to automatically repair broken code builds by analyzing historical data of build errors and their fixes. This model suggests potential fixes to developers directly within their Integrated Development Environment (IDE). In a controlled experiment, the use of these machine learning-suggested fixes improved productivity by reducing active coding and feedback time, and increasing the number of completed code changes.

All-Hands-AI/OpenHands

OpenHands is an AI-powered platform designed to assist with software development, allowing agents to perform tasks similar to human developers. These agents can modify code, run commands, browse the web, call APIs, and even use resources like StackOverflow. OpenHands is easy to set up using Docker and can be run in various modes, including scriptable or interactive CLI.

langgenius/dify

Dify is an open-source platform for developing AI applications, offering an intuitive interface that integrates workflows, agent capabilities, model management, and observability features. Dify's core features include a visual AI workflow builder, integration with numerous LLMs, agent tools, and a retrieval-augmented generation (RAG) pipeline for document handling.

TransformerOptimus/SuperAGI

SuperAGI is an open-source framework designed for developers to create, manage, and run autonomous AI agents. It allows seamless operation of multiple agents simultaneously and provides tools to extend their capabilities. With features like graphical interfaces, performance telemetry, and integration with multiple vector databases, SuperAGI enables AI agents to efficiently handle tasks, learn from experience, and optimize token usage.

lllyasviel/Paints-UNDO

Paints-Undo is an open-source project that provides AI models designed to simulate the drawing process in digital art. By inputting a completed image, users can generate a sequence of steps showing how that image might have been created, mimicking the "undo" function in digital painting software.

Stability-AI/stable-audio-tools

Stable-Audio-Tools is an open-source library for working with audio generation models. It provides tools for training and running models that generate audio, including a Gradio interface for testing. Users can install the library via PyPI, and the repository includes scripts for both training models and performing inference.

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