76-page survey paper on Prompting Techniques ✨ Explores structured understanding and taxonomy of 58 text-only prompting techniques, and 40 techniques for other modalities. 📌 The paper focuses on discrete prefix prompts rather than cloze prompts, because prefix prompts are

Noisy information is not always bad for RAG systems. Well, it depends on what kind of noise. Finally, there is a benchmark (NoiserBench) to measure how different kinds of noisy information affect RAG's performance. It's interesting that out of the different kinds of beneficial

LLMs struggle with fine-grained in-line citations in long-context scenarios. This is a really useful capability but current long-context LLMs don't do so well on fine-grained in-line citations. This new work synthesizes a large-scale SFT dataset with off-the-shelf LLMs to

Protect your swaps from sandwich attacks. 🛡️ You can now safeguard your swap transactions on Jupiter with one click. By turning on ‘MEV Protect’, your transactions will be sent directly to a Jito Labs validator, reducing the chances of your transactions getting frontrun.

Why is decentralization a necessary step for agents to achieve AGI? "For example, even though Google owns the Chrome browser and has access to the most comprehensive web-based temporal action sequence data, lacking annotations for tasks, processes, and reasoning, Gemini cannot

Today would have been the 83rd birthday of Dennis Ritchie, inventor of C and co-creator of Unix: zd.net/2creeZi (Image v/SanderFocus, article v/Jason Perlow (Bluesky, Mastodon, Threads) & ZDNET)

Product, product, product！

How to be part of the Decentralized AGI Ecosystem with coinsfast.fun | watchmovies.lol 🍥 #ai #aigc #web3 #intentagi #decentralizedfinance #actionlayer

How does OpenAI train the Strawberry🍓 (o1) model to spend more time thinking? I read the report. The report is mostly about 𝘸𝘩𝘢𝘵 impressive benchmark results they got. But in term of the 𝘩𝘰𝘸, the report only offers one sentence: "Through reinforcement learning, o1

Agents in Software Engineering Provides a comprehensive overview of frameworks of LLM-based agents in software engineering. arxiv.org/abs/2409.09030

Can LLMs learn to "phone a friend?" 🧵 MIT CSAIL’s new "Co-LLM" algorithm can pair a general-purpose base LLM w/a more specialized model & help them work together. It reviews each token & sees where it needs to call upon an expert, leading to more accurate & efficient replies to

We’re excited to announce that IntentAGI is now ActionLayer! This new name better reflects our vision moving forward.🎉 Check out our updated channels:👇 linktr.ee/actionlayer Thanks for your support! 🌟Stay tuned for more updates!🌟

Convolution Neural Network Cheat Sheet

Transformer by hand✍️ Excel ~ I designed this exercise to show the core math of a Transformer model is to combine columns (attention), combine rows (feed forward), and repeat.👇Join the 'AI Math' community. 👇Download xlsx.

🎮 We're helping shape the future of gaming through our partnership with Solana Labs! At the center of this collaboration is Gameshift, which provides the full slate of Web3 primitives and actions that games require. Learn more → goo.gle/4gACo0f

How can #robots remember? 🤖 💭 For robots to understand and respond to questions that require complex multi-step reasoning in scenarios over long periods of time, we built ReMEmbR, a retrieval-augmented memory for embodied robots. 👀 Technical deep dive from #NVIDIAResearch

The Sam Altman Interview You know him as the CEO of OpenAI — but he's also an avid writer. We spoke not once but twice about how Sam captures ideas, clarifies his thinking, edits his writing, decides what to work on, and uses ChatGPT. Timestamps: 1:47 Will LLMs change how we

The industry is moving from "AI-copilots" to "AI-Agents". ActionLayer believes data annotation plays a crucial role in the development and performance of AI agents. Enabling Machine Understanding: Data annotation provides context and meaning to raw data, allowing AI models to

The era of Action has arrived. Stay tuned, more is coming..... #Ai#action#agent