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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 customary. See also SD2, SDXL, SD3 papers. Imagen / Imagen 2 / Imagen 3 paper - Google’s image gen. See also Ideogram. AlphaCodeium paper - Google revealed AlphaCode and AlphaCode2 which did very nicely on programming issues, however right here is a method Flow Engineering can add much more performance to any given base mannequin. While we now have seen makes an attempt to introduce new architectures similar to Mamba and more not too long ago xLSTM to only identify a number of, it seems seemingly that the decoder-solely transformer is here to remain - at the least for probably the most part. While the researchers had been poking round in its kishkes, additionally they came across one different interesting discovery. We covered many of those in Benchmarks 101 and Benchmarks 201, whereas our Carlini, LMArena, and Braintrust episodes covered non-public, area, 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 model irrelevant in about two years’ time. Introduction to Information Retrieval - a bit unfair to advocate a e-book, however we try to make the purpose that RAG is an IR downside and IR has a 60 12 months history that features TF-IDF, BM25, FAISS, HNSW and other "boring" methods.

The unique authors have started Contextual and have coined RAG 2.0. Modern "table stakes" for RAG - HyDE, chunking, rerankers, multimodal knowledge are better introduced elsewhere. No, they are the responsible ones, those who care enough to call for regulation; all the higher if considerations about imagined harms kneecap inevitable opponents. Cursor AI vs Claude: Which is healthier for Coding? SWE-Bench is more well-known for coding now, however is expensive/evals brokers slightly than fashions. Technically a coding benchmark, however more a take a look at of agents than uncooked LLMs. We lined most of the 2024 SOTA agent designs at NeurIPS, and you could find more readings in the UC Berkeley LLM Agents MOOC. FlashMLA focuses on optimizing the decoding process, which might significantly improve the processing pace. Anthropic on Building Effective Agents - simply a great state-of-2024 recap that focuses on the importance of chaining, routing, parallelization, orchestration, evaluation, and optimization. Orca 3/AgentInstruct paper - see the Synthetic Data picks at NeurIPS but this is a great way to get finetue knowledge. The Stack paper - the unique open dataset twin of The Pile focused on code, starting a terrific lineage of open codegen work from The Stack v2 to StarCoder.

Open Code Model papers - select from DeepSeek online-Coder, Qwen2.5-Coder, or CodeLlama. LLaMA 1, Llama 2, Llama three papers to grasp the leading open fashions. The helpfulness and security reward models had been trained on human choice knowledge. The post-training also makes a hit in distilling the reasoning functionality from the Free DeepSeek online-R1 series of models. R1's success highlights a sea change in AI that would empower smaller labs and researchers to create competitive fashions and diversify the choices. Consistency Models paper - this distillation work with LCMs spawned the fast draw viral second of Dec 2023. These days, updated with sCMs. We started with the 2023 a16z Canon, but it wants a 2025 update and a sensible focus. ReAct paper (our podcast) - ReAct began a long line of research on tool utilizing and function calling LLMs, together with Gorilla and the BFCL Leaderboard. The EU has used the Paris Climate Agreement as a software for economic and social control, causing harm to its industrial and business infrastructure additional helping China and the rise of Cyber Satan because it might have happened within the United States with out the victory of President Trump and the MAGA movement. LlamaIndex (course) and LangChain (video) have maybe invested essentially the most in academic resources.

The launch of a brand new chatbot by Chinese artificial intelligence agency DeepSeek triggered a plunge in US tech stocks because it appeared to carry out in addition to OpenAI’s ChatGPT and other AI models, but utilizing fewer assets. The startup stunned the Western and far Eastern tech communities when its open-weight model DeepSeek-R1 triggered such an unlimited wave that Free DeepSeek online appeared to problem Nvidia, OpenAI and even Chinese tech giant Alibaba. See also 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 associated to malware creation however stopped short of offering a transparent "how-to" information. With Gemini 2.Zero also being natively voice and imaginative and prescient multimodal, the Voice and Vision modalities are on a transparent path to merging in 2025 and past. This may enable a chip like Sapphire Rapids Xeon Max to hold the 37B parameters being activated in HBM and the remainder of the 671B parameters would be in DIMMs. Non-LLM Vision work remains to be essential: e.g. the YOLO paper (now as much as v11, but mind the lineage), but increasingly transformers like DETRs Beat YOLOs too. Certainly one of the most well-liked developments in RAG in 2024, alongside of ColBERT/ColPali/ColQwen (more in the Vision part).

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