/
Navigation
Chronicles
Browse all articles
Explore
Semantic exploration
Research
Entity momentum
Nexus
Correlations & relationships
Story Arc
Topic evolution
Drift Map
Semantic trajectory animation
Posts
Analysis & commentary
Pulse API
Tech news intelligence API
Browse
Entities
Companies, people, products, technologies
Domains
Browse by publication source
Handles
Browse by social media handle
Detection
Concept Search
Semantic similarity search
High Impact Stories
Top coverage by position
Sentiment Analysis
Positive/negative coverage
Anomaly Detection
Unusual coverage patterns
Analysis
Rivalry Report
Compare two entities head-to-head
Semantic Pivots
Narrative discontinuities
Crisis Response
Event recovery patterns
Connected
Search: /
Command: ⌘K
Embeddings: large
TEXXR

Chronicles

The story behind the story

days · browse · Enter similar · o open

Microsoft releases Phi-2, an AI language model the company says outperforms Mistral and Llama 2 at 7B and 13B parameters and is small enough to run on a phone

Carl Franzen / VentureBeat :

VentureBeat Carl Franzen

Discussion

  • @vitor_dlucca Vitor de Lucca on threads
    Yesterday, new Mistral killed Gemini Pro.  Today, Microsoft showed us that GPT4 Turbo with proper prompting is better than Gemini Ultra.  Microsoft also launched Phi-2.  A small LLM (2.7b) that beat Gemini Nano (3.2b), Mistral 7b, and beat llama 70b on coding.
  • @msftresearch @msftresearch on x
    Today, we share our teams' latest contributions, Phi-2 and promptbase. Phi-2 outperforms other existing small language models, yet it's small enough to run on a laptop or mobile device. https://www.microsoft.com/...
  • @sebastienbubeck Sebastien Bubeck on x
    Phi-2 numbers, finally! We're seeing a consistent ranking: phi-2 outperforms Mistral 7B & Gemini Nano 2* (*on their reported benchmarks) and is roughly comparable to Llama 2-70B (sometimes better, sometimes worse). Beyond benchmarks, playing with the models tells a similar story.…
  • @marktenenholtz Mark Tenenholtz on x
    Microsoft just released Phi-2 (2.7B) which seems to come close to Llama 70B. It's trained on 1.4T tokens of heavily filtered web data and a lot of GPT 3.5/4 outputs. Knowledge distillation really does work, and combining it with other high quality data could be the key for OSS. […
  • @andrewcurran_ Andrew Curran on x
    Phi-2 was trained on 1.4T tokens, the training took 14 days on 96 A100 GPUs. They claim to have already surpassed Google Nano despite being a smaller size. [image]
  • @linusekenstam Linus on x
    Phi-2 A new large language model that beats its rivaling 25x larger counterpart. What else? It runs on your mobile device. Truly personal LLM's that work offline using edge compute is here https://www.microsoft.com/... [image]
  • @erichorvitz Eric Horvitz on x
    More https://www.microsoft.com/... on promptbase & advances in prompting, including how we steered GPT-4 to record performance on the Measuring Massive Multitask Language Understanding (MMLU) benchmark, spanning 57 areas @satyanadella @kevin_scott @peteratmsr @HarshaNori @MSFTRes…
  • @emostaque @emostaque on x
    Smol models ftw [image]
  • @richinseattle Richard Johnson on x
    Contrary to rumors, I assure you the Phi-2 model is downloadable, but it is against the license to redistribute it. You can login to Azure ML Studio (free with a basic Azure account), select it from the Model Catalog, and then download the files from the Artifacts tab. [image]
  • @sebastienbubeck Sebastien Bubeck on x
    Sorry I know it's a bit confusing: to download phi-2 go to Azure AI Studio, find the phi-2 page and click on the “artifacts” tab. See picture. [image]
  • @satyanadella Satya Nadella on x
    From new best-in-class small language models to state-of-the-art prompting techniques, we're excited to share these innovations and put them in the hands of researchers and developers.
  • @alphasignalai Lior on x
    Microsoft just released Phi-2, a 2.7B LLM that rivals the 25x bigger LLaMa-2 70B. The best part? The model is small enough to run on a laptop or mobile device. Trained on 1.4T tokens: mixture of synthetic & web datasets, it beats Mistral 7B and Llama-2-70B model on muti-step... […
  • @simonw Simon Willison on x
    Anyone figured out how to run Microsoft's new Phi-2 LLM on a Mac yet? https://www.microsoft.com/...