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This month is buzzing with AI innovation—from can’t-miss conferences to game-changing GenAI use cases. Whether you're looking to level up your skills, explore new tools, or stay ahead of the curve, we've got you covered.
LLM Expert Insights,
Packt
Breakthroughs in AI are made possible through years of study, experimentation, and research that eventually shape the mainstream. Whether you're a researcher pushing the boundaries of machine learning, a developer building with generative AI, or a leader shaping enterprise strategy, this handpicked list of the top conferences in 2025 will help you stay connected to the pulse of innovation.
1. CVPR 2025 – IEEE/CVF Conference on Computer Vision and Pattern Recognition
Dates: June 11–15, 2025
Location: Music City Center, Nashville, TN, USA
Cost: In-person - General: $900; Student: $810; IEEE/CVF Members ($900 for professionals, $675 for students)
Nature: Virtual - General: $215; Student: $125; IEEE/CVF Members ($180 for professionals, $100 for students)
Focus: Computer vision, multimodal AI, LLMs in vision tasks
Website: CVPR 2025 Conference
2. ICLAD 2025 – IEEE International Conference on LLM-Aided Design
Dates: June 26–27, 2025
Location: Paul Brest Hall, Stanford University, Stanford, CA
Cost: In-person only - General: $600; Student: $410; IEEE/CVF Members ($500 for professionals, $350 for students)
Focus: Utilizing large language models to enhance design processes in circuits, software, and computing systems
3. ICML 2025 – International Conference on Machine Learning
Dates: July 13–19, 2025
Location: Vancouver Convention Center, Vancouver, Canada
Cost: In-person - General: $1365; Student: $1030
Nature: Virtual - General: $275; Student: $200
Focus: Machine learning theory and practice, generative AI, LLMs
Website: ICML 2025 Conference
4. ACL 2025 – 63rd Annual Meeting of the Association for Computational Linguistics
Dates: July 27 – August 1, 2025
Location: Vienna, Austria
Cost: In-person - General: $1125; Academic: $800; Student: $425 + ACL Membership fee ($100 for professionals, $50 for students)
Nature: Virtual: - General: $550; Academic: $400; Student: $250 + ACL Membership fee ($100 for professionals, $50 for students)
Focus: Natural language processing, large language models, language generation
Website: ACL 2025
5. NeurIPS 2025 – Conference on Neural Information Processing Systems
Dates: December 2–7, 2025
Location: San Diego Convention Center, San Diego, CA, USA
Cost: In-person - General: $1000; Academic: $800; Student: $375
Nature: Virtual - General: $275; Academic: $200; Student: $50
Focus: Advanced ML research, LLMs, multimodal AI
Website: NeurIPS 2025 Conference
The hype around GenAI and how it enhances productivity shows no signs of slowing down. Just as previous generations shifted from Xeroxing to Googling, we now find ourselves firmly in the era of “Ask ChatGPT.”.
GenAI finds its applications in various fields, such as image synthesis and text generation to music composition, marketing content, data analysis, coding, and countless other tasks that, until recently, required specialized expertise. In this issue, we spotlight just a few of the many real-world applications of GenAI, using OpenAI’s ChatGPT as our lens.
1. Daily assistant: ChatGPT is an excellent tool for boosting your day-to-day activities, such as grocery shopping, meal planning, and workouts, among many other tasks. Take, for example, the following prompt:
Generate a 75’ workout routine for strength training. My goal is increasing my overall strength and also improving flexibility. I need a workout for the upper body only divided by the muscle group. Make it in a table format with # of reps and # of series. Make sure to incorporate some rest as well.
Here is a sample workout plan that ChatGPT might generate for you:
2. Creating content: You can use ChatGPT to craft emails, create social media posts, write blogs and articles, assist with proofreading, perform translations, analyze documents, or even adjust the tone of your content: whether you want it to be formal, quirky, casual, or sarcastic. Take a look at ChatGPT’s sarcastic translation of an Italian text:
3. Coding assistant: The primary capability you should leverage is ChatGPT’s code generation. From writing a simple function to creating the skeleton of a game, ChatGPT can provide enough building blocks to get started. You can also use it to suggest code optimizations, explain errors, and debug your existing code. Additionally, it can help generate documentation, improve code explainability, and even assist in understanding the structure of a neural network. Take, for example, the following CNN model:
If you ask ChatGPT to explain this model, it may respond as follows:
4. Design marketing campaigns: Suppose you have a new product and need a go-to-market (GTM) strategy. You can ask ChatGPT to help you draft an initial plan. Then, by iteratively refining your prompts, you can request suggestions for the product name, marketing hook, target audience research, unique value proposition, sales channels, pricing, SEO keywords, and more. You can even ask it to generate product launch posts. Here are some of the prompts Valentina experimented with in her book while developing a GTM strategy for eco-friendly socks.
Beyond the four use cases we’ve spotlighted in this issue, the book Practical Generative AI with ChatGPT, by Valentina Alto, introduces generative AI and its applications, focusing on OpenAI’s ChatGPT. It covers prompt engineering, daily productivity use cases, domain-specific applications for developers, marketers, and researchers, and the creation of custom GPTs using the GPT Store, enabling specialized assistants without coding, powered by personalized instructions and tools.
Let’s get right into it.
Google DeepMind Introduces Gemini 2.5 with Native Audio Capabilities
Google DeepMind has launched Gemini 2.5, now capable of processing real-time audio and video. The model can interpret screen-shared content, respond to tone and background noise, and supports over 24 languages, making it more contextually aware and interactive than ever before.
Amazon to Test Humanoid Robots for Package Deliveries
The Information has reported that Amazon is preparing pilot tests of Agility Robotics' bipedal humanoid robot, Digit, for use in logistics and package handling. Designed to work safely in spaces designed for humans, Digit is expected to automate repetitive warehouse tasks and even assist in last-mile delivery operations.
OpenAI Launches Coordinated Vulnerability Disclosure Framework
OpenAI has introduced an “Outbound Coordinated Vulnerability Disclosure” policy to responsibly report security issues it uncovers in external systems. This move aims to bolster security standards and transparency across the tech ecosystem.
DeepSeek’s New AI Sparks Free Speech Concerns
Chinese AI developer DeepSeek has triggered global criticism for its model’s extreme content filtering. Users attempting to query politically sensitive topics, like Tiananmen Square or Taiwanese independence, are met with complete denials, spotlighting a stark divide in global AI moderation norms.
Nvidia Blackwell Chips Dominate New MLPerf Benchmarks
Nvidia’s Blackwell GPUs dominated the latest MLPerf training benchmarks, delivering double the performance of previous H100 chips. These results highlight Blackwell’s efficiency in training large AI models with fewer GPUs, reduced energy use, and lower costs, solidifying Nvidia’s leadership in AI hardware and accelerating industry-wide adoption of its new architecture.
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Thanks for reading and have a great day!
That’s a wrap for this week’s edition of AI_Distilled 🧠⚙️
We would love to know what you thought—your feedback helps us keep leveling up.
Thanks for reading,
The AI_Distilled Team
(Curated by humans. Powered by curiosity.)