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DeepSeek V1, Coder, Math, MoE, V2, V3, R1 papers. Many embeddings have papers - choose your poison - SentenceTransformers, OpenAI, Nomic Embed, Jina v3, cde-small-v1, ModernBERT Embed - with Matryoshka embeddings increasingly normal. See also SD2, SDXL, SD3 papers. Imagen / Imagen 2 / Imagen 3 paper - Google’s picture gen. See additionally Ideogram. AlphaCodeium paper - Google printed AlphaCode and AlphaCode2 which did very properly on programming problems, but here is one way Flow Engineering can add much more performance to any given base model. While we have now seen makes an attempt to introduce new architectures such as Mamba and more recently xLSTM to simply name a number of, it appears possible that the decoder-only transformer is right here to remain - at the very least for probably the most half. While the researchers had been poking round in its kishkes, additionally they got here across one other interesting discovery. We coated many of those in Benchmarks a hundred and one and Benchmarks 201, whereas our Carlini, LMArena, and Braintrust episodes covered personal, arena, and product evals (learn LLM-as-Judge and the Applied LLMs essay). The drop means that ChatGPT - and LLMs - managed to make StackOverflow’s business mannequin irrelevant in about two years’ time. Introduction to Information Retrieval - a bit unfair to suggest a e book, but we are attempting to make the point that RAG is an IR drawback and IR has a 60 yr historical past that includes TF-IDF, BM25, FAISS, HNSW and other "boring" techniques.

The original authors have started Contextual and have coined RAG 2.0. Modern "table stakes" for RAG - HyDE, chunking, rerankers, multimodal information are better offered elsewhere. No, they're the responsible ones, the ones who care sufficient to name for regulation; all the higher if concerns about imagined harms kneecap inevitable competitors. Cursor AI vs Claude: Which is healthier for Coding? SWE-Bench is extra well-known for coding now, but is costly/evals brokers moderately than models. Technically a coding benchmark, but extra a check of brokers than uncooked LLMs. We lined lots of the 2024 SOTA agent designs at NeurIPS, and you could find more readings within the UC Berkeley LLM Agents MOOC. FlashMLA focuses on optimizing the decoding process, which can significantly improve the processing pace. Anthropic on Building Effective Agents - just an ideal state-of-2024 recap that focuses on the significance of chaining, routing, parallelization, orchestration, analysis, and optimization. Orca 3/AgentInstruct paper - see the Synthetic Data picks at NeurIPS but this is a great strategy to get finetue data. The Stack paper - the original open dataset twin of The Pile focused on code, beginning an important lineage of open codegen work from The Stack v2 to StarCoder.

Open Code Model papers - choose from DeepSeek-Coder, Qwen2.5-Coder, or CodeLlama. LLaMA 1, Llama 2, Llama 3 papers to know the main open fashions. The helpfulness and security reward fashions have been skilled on human choice knowledge. The put up-training also makes successful in distilling the reasoning functionality from the DeepSeek-R1 sequence of fashions. R1's success highlights a sea change in AI that might empower smaller labs and researchers to create aggressive fashions and diversify the options. Consistency Models paper - this distillation work with LCMs spawned the quick draw viral second of Dec 2023. Today, updated with sCMs. We started with the 2023 a16z Canon, but it surely needs a 2025 update and a practical focus. ReAct paper (our podcast) - ReAct began a protracted line of analysis on tool using and operate calling LLMs, including Gorilla and the BFCL Leaderboard. The EU has used the Paris Climate Agreement as a device for economic and social control, inflicting harm to its industrial and enterprise infrastructure additional helping China and the rise of Cyber Satan as it could have occurred within the United States with out the victory of President Trump and the MAGA movement. LlamaIndex (course) and LangChain (video) have maybe invested the most in instructional sources.

The launch of a brand new chatbot by Chinese artificial intelligence firm DeepSeek online triggered a plunge in US tech stocks because it appeared to carry out as well as OpenAI’s ChatGPT and different AI models, but using fewer resources. The startup stunned the Western and much Eastern tech communities when its open-weight model DeepSeek-R1 triggered such a vast wave that DeepSeek appeared to challenge Nvidia, OpenAI and even Chinese tech large Alibaba. See additionally Lilian Weng’s Agents (ex OpenAI), Shunyu Yao on LLM Agents (now at OpenAI) and Chip Huyen’s Agents. Essentially, the LLM demonstrated an awareness of the ideas related to malware creation but stopped in need of offering a clear "how-to" information. With Gemini 2.Zero also being natively voice and vision multimodal, the Voice and Vision modalities are on a clear path to merging in 2025 and past. This may permit a chip like Sapphire Rapids Xeon Max to hold the 37B parameters being activated in HBM and the remainder of the 671B parameters can be in DIMMs. Non-LLM Vision work is still essential: e.g. the YOLO paper (now up to v11, but thoughts the lineage), but increasingly transformers like DETRs Beat YOLOs too. Considered one of the most popular tendencies in RAG in 2024, alongside of ColBERT/ColPali/ColQwen (extra within the Vision section).

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