a llama standing next to a large monitor full of computer code. large text label reads “Tech” –chaos 20 –ar 4:3 –style raw –personalize ytt1577 –v 6.1
“Drowning in AI jargon? We’ve got you covered! 🌊📚 A good AI cheat sheet to boost your AI literacy today.
“🛠️ Seamless LangSmith tracing in LangGraph.js 🕸️ You can now use LangSmith to trace arbitrary functions and SDKs in LangGraph.js with no additional configuration! If you prefer using model SDKs directly, it’s now easier than ever to use LangSmith’s tracing, evaluation, and
“🚀 Introducing the Model Drops Tracker! 🕵️♂️ Feeling overwhelmed by the AI model release frenzy? 🤯 You’re not alone! I built this simple tool to help us all keep up: – Filter recent models from the @huggingface Hub – Set minimum likes threshold – Choose how recent you want to go
Workera Launches New, Free Skill Assessments for
“It’s been a little longer than usual since my last post, but I’ve been writing! My long-form writeup on everything you need to know about LLM-as-a-judge is out now… Why is LLM-as-a-Judge so popular? LLM-as-a-Judge evaluates the quality of an LLM’s output by prompting another,
“figuring out good prompts is only half the battle, the best AI implementations include multiple layers and feedback loops that need to work in concert with one another, all prone to breaking in weird ways” / X
Working with AI (Part 2): Code Conversion
“Synthetic data can beat its teacher! The AI-MO team released their winning dataset with an additional fine-tuned @Alibaba_Qwen 2 model that approaches or surpasses @OpenAI GPT-4o and @AnthropicAI Claude 3.5 in match competitions. 👀 There was a sentiment that fine-tuned models
“A new paper suggests too much training on AI-produced content causes AI models to break. This is an ongoing discussion, with lots of research and discussion about when/if synthetic training data works. So a helpful paper, but likely not the final word.
“There is still no benchmark for LLM hallucination rates. Few benchmarks have comparisons to humans There are no common benchmarks that cover use cases in innovation, writing, persuasion, human interaction, education, creativity, etc. Yet LLMs are often built towards benchmarks” / X
How to Create High Quality Synthetic Data for Fine-Tuning LLMs
“Patronus AI announced the release of ‘Lynx’, a new open-source hallucination detection model They claim that it outperforms existing AI models such as GPT-4, Claude-3-Sonnet, and more An important challenge to solve
Building A Generative AI Platform
“”Intelligence Destruction Cycle” (IDC), a novel framework for understanding the rapid obsolescence and replacement of artificial intelligence models in the current AI research landscape. Drawing inspiration from Schumpeter’s theory of creative destruction, the IDC posits that the” / X
Three Archetypes of AI Application Startups
“A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data Despite the availability of international prize-money competitions, scaled vehicles, and simulation environments, research on autonomous racing and the control of sports cars operating close to the limit of
An Update on our Make Designs Feature | Figma Blog
[2403.19967v1] Rewrite the Stars
[2404.05218v1] Multi-agent Long-term 3D Human Pose Forecasting via Interaction-aware Trajectory Conditioning
[2407.13623] Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies
[2407.15773v1] STAMP: Outlier-Aware Test-Time Adaptation with Stable Memory Replay
[2407.16312v1] MOMAland: A Set of Benchmarks for Multi-Objective Multi-Agent Reinforcement Learning
[2407.16375v1] Ranking protein-protein models with large language models and graph neural networks
[2407.16957v1] Raindrop Clarity: A Dual-Focused Dataset for Day and Night Raindrop Removal
[2407.16993v1] LoFormer: Local Frequency Transformer for Image Deblurring
[2407.17418v1] 3D Gaussian Splatting: Survey, Technologies, Challenges, and Opportunities
“@Laz4rz Lack of standardization in the benchmarks. To be fair, MMLU is not that bad compared to many other evals” / X
Optimizing LLMs for Cost and Quality with OctoAI’s Experts | OctoAI
“Composable optimizers over modular NLP programs are the future! If familiar w/ DSPy lingo, you should compose BootstrapFewShot-based optimizers (like RS or bayesian MIPRO) with BootstrapFinetune! Follow @dilarafsoylu for her DSPy optimizer releases soon!
“🚨When building LM systems for a task, should you explore finetuning or prompt optimization? Paper w/ @dilarafsoylu @ChrisGPotts finds that you should do both! New DSPy optimizers that alternate optimizing weights & prompts can deliver up to 26% gains over just optimizing one!
Heads up! You’ve scrolled to the end of this category. There may have been just one or two links (above), so go back up and double check to be sure you didn’t quickly scroll down past it.
Be Sure To Read This Week’s Main Post:
This week’s executive overview and top links are here:
AI News #43: Week Ending 07/26/2024 with Executive Summary and Top 97 Links
The post you just read is an deep dive extension of my weekly newsletter, This Week In AI, an executive summary of the top things to know in AI. Each week, I create an accessible overview for laypeople to feel confident they are conversant with the week’s AI developments. I include a curated list of must-click links of the week, to offer everyone a hands-on opportunity to explore the most intriguing updates in artificial intelligence across various categories, including robotics, imagery, video, AR/VR, science, ethics, and more. Beyond the overview, I post these topic-based deeper dives (below). If you haven’t read this week’s overview, I recommend starting there.
- Agents/Copilots
- Amazon
- Apple
- Artificial General Intelligence (AGI)
- Augmented and Virtual Reality (AR/VR)
- Autonomous Vehicles
- AI Audio
- Business and Enterprise AI
- Chips and Hardware
- Consumer Products
- Education
- Ethics/Legal Security
- Images/Photos
- International AI News
- Locally Run AI Models
- Mobile
- Meta
- Microsoft
- OpenAI
- Open Source
- Podcasts/YouTube
- Publishing and News
- Retrieval-Augmented Generation (RAG) News
- Robots and Embodiment
- Safe Intelligence, Inc.
- Science and Medicine
- Video
- Vision/Multimodality
- X/Twitter/Grok
- Tech and Development
Credits/Sources
Most of these weekly links come from just a few prolific oversharing sources. Please follow them, as they work hard to find the news each week and they make it a lot easier for me to compile.
- Robert Scoble: https://x.com/Scobleizer
- Ethan Mollick: https://www.linkedin.com/in/emollick/
- Alan Thompson: https://lifearchitect.ai/
- Theoretically Media: https://www.youtube.com/@TheoreticallyMedia
- The Rundown: https://www.therundown.ai/
- Bilawal Sidhu: https://twitter.com/bilawalsidhu/
- TLDR: https://tldr.tech/ai
- Jeremiah Owyang: https://twitter.com/jowyang
- Nick St. Pierre: https://twitter.com/nickfloats
- Dr. Jim Fan: https://twitter.com/DrJimFan
- All About AI: https://www.youtube.com/@AllAboutAI
- Marshall Kirkpatrick: https://aitimetoimpact.com/
- AI News (Smol Talk): https://buttondown.email/ainews/archive/
- Andrej Karpathy: https://x.com/karpathy
- Brett Adcock: https://x.com/adcock_brett
- Florent Daudens: https://x.com/fdaudens
- Ate-a-Pi: https://x.com/8teAPi
- Francesco Marconi: https://x.com/fpmarconi
For previous issues, please visit the archives!
Thanks for reading!
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