Search: “index”

DeepSeek is becoming more popular among US enterprises as companies look for cheaper alternatives to Anthropic and OpenAI “DeepSeek takes top spot on 'trending' list as companies look for alternatives

As you can see It does seem like meaningfully better AI releases are accelerating, especially from OpenAI & Anthropic. To illustrate, I caused this timeline to be created. It only lists new models tha

Introducing AI IQ Bio: the most comprehensive set of biotech benchmarks in the world ...& Bio IQ: the most comprehensive 'biotech capabilities index' ever produced Benchmark sources include benchmarks

Can’t tell if the PR reads more like a security incident or a product release… We suspected last week's cyberattack might have come from a frontier lab, given the sophistication of the agent. Turns ou

Incredible Introducing the world's fastest tokenizer implementation, Gigatoken! Gigatoken is ~500-1000x faster than HuggingFace, and ~100x faster than OpenAI's tiktoken for most tokenizer definitions

OpenAI has collaborated with Microsoft’s Bing while also running its own web‑crawling and indexing systems, and Anthropic similarly relies on search‑derived data. Both firms prominently incorporate se

Simon Willison notes that both Anthropic and OpenAI build products that rely heavily on searching data but keep the underlying search index they use hidden from public view. He finds it surprising how

verbalizing one of those aha moments i had that seems retroactively pretty obvious: if you prioritize pretrain data quality enough that commoncrawl isn't good enough for you, you have to build a Whole

The team at @llama_index built an awesome template using LlamaParse and the new Managed Agents in the Gemini API. See how they built an agent that can tackle unstructured documents. 📄↓ 🚀 The team at @

Document Parsing + Gemini 🔥 Excited to collaborate with the Google team on this, here's to many more! The team at @llama_index built an awesome template using LlamaParse and the new Managed Agents in

Your AI chatbot is only as good as the data behind it. This n8n template from our friends at @apify shows you how to wire up a RAG pipeline using Apify + Pinecone + Gemini so your chatbot can answer q

GLM-5.2 leads open weights models and sits at #3 overall on GDPval-AA, a real-world agentic work benchmark GLM-5.2 from @Zai_org scores 1524 Elo on GDPval-AA, which measures performance on real-world,

Your coding agent doesn't need to leave the terminal to use Pinecone. We now ship official plugins and skills for the agentic IDEs and CLIs you are already building in: Claude Code, Cursor, GitHub Cop

We benchmarked Opus 5 comprehensively on document understanding through ParseBench. It is roughly on par with Opus 4.8 - it does a few points worse on dense tables, but does slightly better on parsing

Running fast is not enough, you need fast AND correct An excellent addition from @ArtificialAnlys to make sure that the flashy speed numbers are backed by 100% matching accuracy Announcing the Artific

Meta returns to open weights: Muse Glimmer, its first open-weights release since Llama 4, scores 35 on the Artificial Analysis Intelligence Index. It is a 30B-parameter model, and the first from Meta

As you are hiring AI people, look for folks who have kept up with the trajectory of the industry, especially OSS. Someone who has their ear to the ground. Things are moving FAST. (deepagents existed ~

How do you trace one number in a 200 page ESG report back to the exact page it came from? We dug into that with the @llama_index team behind LiteParse. We tested five ways to retrieve evidence across

Can’t tell if the PR reads more like a security incident or a product release… We suspected last week's cyberattack might have come from a frontier lab, given the sophistication of the agent. Turns ou

Incredible Introducing the world's fastest tokenizer implementation, Gigatoken! Gigatoken is ~500-1000x faster than HuggingFace, and ~100x faster than OpenAI's tiktoken for most tokenizer definitions

We benchmarked Opus 5 comprehensively on document understanding through ParseBench. It is roughly on par with Opus 4.8 - it does a few points worse on dense tables, but does slightly better on parsing

The future of FDE work seems closely related with all work around evals/posttraining/RL envs. FDEs are effectively responsible for the following: 1. Define the business problem. 2. Codify the business

Meta returns to open weights: Muse Glimmer, its first open-weights release since Llama 4, scores 35 on the Artificial Analysis Intelligence Index. It is a 30B-parameter model, and the first from Meta

Whoa, Meta released a new open-weight LLM yesterday, something that hasn't happened since the good old Llama days. Their Meta Muse Glimmer model is a 30B multimodal reasoning model with a Gemma-like a

We benchmarked Opus 5 comprehensively on document understanding through ParseBench. It is roughly on par with Opus 4.8 - it does a few points worse on dense tables, but does slightly better on parsing

Grok 4.3 - excellent intelligence per unit cost xAI has launched Grok 4.3, achieving 53 on the Artificial Analysis Intelligence Index with improved agentic performance, ~40% lower input price, and ~60

Google’s new Gemini 3.5 Flash is the clear leader on the Intelligence vs Speed Pareto frontier and makes large gains on GDPval-AA (real-world agentic tasks), but is 5x the cost of Gemini 3 Flash @Goog

The MongoDB plugin in Grok Build enables users to query data, optimize database indexes, and perform database management tasks directly within the Grok interface. This integration allows developers to

Grok 4.5 context window will upgrade to 1M probably by next week SpaceXAI’s Grok 4.5 scores 54 to place fourth on the Artificial Analysis Intelligence Index following only Fable 5, GPT-5.5, and Opus 4

Grok 4.5 brings frontier performance across coding and knowledge work SpaceXAI’s Grok 4.5 scores 54 to place fourth on the Artificial Analysis Intelligence Index following only Fable 5, GPT-5.5, and O

Grok is the Flow LLM. Grok 4.5’s biggest advantage is its speed. It’s smart enough to be comparable to the other models on most things. But that speed allows you to make little tweaks to your system s

Kimi K3 is second only to Fable 5 on AA-Briefcase, our agentic knowledge work benchmark, but costs more than Opus 4.8 to run while averaging nearly an hour per task Last week @Kimi_Moonshot released K

Alibaba has released Qwen Audio 3.0 Realtime, with the Plus variant debuting as the new #1 model on the Artificial Analysis Speech to Speech Index at 84.1%, ahead of GPT-Realtime-2.1 High at 79.1% Rel

Kimi K2.6, a language model developed by Moonshot AI, has achieved the top ranking on the open-weight category of the Vals Index benchmark, while placing 7th overall across all model categories. The V

DeepSeek V4 by @deepseek_ai just dropped! SGLang is ready on Day 0 with a full stack of optimizations from architectures to low-level kernels. We also deliver a verified RL training pipeline in Miles

🎉 Day-0 support for @deepseek_ai V4 Pro and Flash on vLLM — a new generation of DeepSeek model, purpose-built for tasks up to 1M tokens. Alongside the release, we're publishing a first-principles walk

Local open-weight AI on a laptop has been improving more than twice as fast as Moore's Law! Between May 2024 and May 2026, the most expensive MacBook Pro you could buy stayed at 128 GB of unified memo

DeepSeek is becoming more popular among US enterprises as companies look for cheaper alternatives to Anthropic and OpenAI “DeepSeek takes top spot on 'trending' list as companies look for alternatives

LLM Wikis are being slept on. I argue that creating knowledge bases with LLMs or coding agents is one of the most valuable applications of AI today. It's about being intentional in building and scalin

Running fast is not enough, you need fast AND correct An excellent addition from @ArtificialAnlys to make sure that the flashy speed numbers are backed by 100% matching accuracy Announcing the Artific

Sub-32B open weights models now offer GPT-5 level intelligence with Qwen3.5 27B (Reasoning) matching GPT-5 (medium) at 42 and Gemma 4 31B (Reasoning) matching GPT-5 (low) at 39 on the Artificial Analy

@lmsysorg @sgl_project @vllm_project @CoreWeave @nebiusai @nscale @togethercompute @Togethercompute enables AI labs and enterprises to run frontier models and agents on the NVIDIA Blackwell platform—g

Oh look! Anthropic's entire 'we are delaying Mythos' narrative was marketing hogwash. Kudos to FT for confirming what was obvious. Anthropic simply doesn't have the compute. FT: 'Multiple people with

🎉 Day-0 support for @deepseek_ai V4 Pro and Flash on vLLM — a new generation of DeepSeek model, purpose-built for tasks up to 1M tokens. Alongside the release, we're publishing a first-principles walk

Launching pyptx — a Python DSL for writing NVIDIA PTX kernels. One PTX instruction = one Python call. Write pure PTX in Python. Direct Hopper + Blackwell support: wgmma, TMA, tcgen05, mbarriers. JAX +

Me, 2024. LLMs will be commodity; (except for Nvdia) profits will be hard to squeeze out. Techbros: Shut up, Gary. GPT-5 is gonna be AGI. Today: LLMs are commodity; (except for Nvidia) profits have be

Meta returns to open weights: Muse Glimmer, its first open-weights release since Llama 4, scores 35 on the Artificial Analysis Intelligence Index. It is a 30B-parameter model, and the first from Meta

Whoa, Meta released a new open-weight LLM yesterday, something that hasn't happened since the good old Llama days. Their Meta Muse Glimmer model is a 30B multimodal reasoning model with a Gemma-like a