Matt Henderson @matthen2
maths, visualisations, conversational AI. currently @RekaAILabs - previously: @Apple AI/ML, @PolyAI, @GoogleAI, MSc @EdinburghUni, PhD @Cambridge_Eng matthen.com Edinburgh, UK Joined February 2010-
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Matt Henderson retweeted
🔥Newly updated scores for Reka Core, Flash and Edge on MMMU leaderboard: mmmu-benchmark.github.io.
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Matt Henderson retweeted
Reka Core, Flash, and Edge A Series of Powerful Multimodal Language Models We introduce Reka Core, Flash, and Edge, a series of powerful multimodal language models trained from scratch by Reka. Reka models are able to process and reason with text, images, video, and audio
our tech report has a lot of interesting details (it’s a lot more than a marketing release typeset in latex.. 😄)
our tech report has a lot of interesting details (it’s a lot more than a marketing release typeset in latex.. 😄)
ask an LLM to generate a list of random words, and each one gives you its own distribution
Matt Henderson retweeted
no matter how chaotic and unstable the orbits of these three gravitational bodies are, their centre of gravity (centroid of the triangle) always remains stationary and fixed in space
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Lidiya Murakhovs'ka �.. @murakhovska
204 Followers 877 Following Applied Scientist @SFResearch, working on conversational AI.
Persuaded or manipulated by AI? Check out this new paper from @GoogleDeepMind on definitions and mitigations. It was a privilege to advise on this important research! #AIethics #PersuasionAI
🔮 New Google DeepMind paper exploring what persuasion and manipulation in the context of language models. 👀 Existing safeguard approaches often focus on harmful outcomes of persuasion. This research argues for a deeper examination of the process of AI persuasion itself to…
question: i’m finetuning embedding models for a retrieval. i found large T5 encoders from GTR and SentenceT5 families significantly underperform BERT base how is this possible? feels it must be hyperparameters? unless i found the one NLP task ever where scaling doesn’t help
Reka core model is out with impressive metrics! Excited to partner with @DaniYogatama and the @RekaAILabs team to bring Reka core to @SnowflakeDB #Cortex.
Meet Reka Core, our best and most capable multimodal language model yet. 🔮 It’s been a busy few months training this model and we are glad to finally ship it! 💪 Core has a lot of capabilities, and one of them is understanding video --- let’s see what Core thinks of the 3 body…
And #SnowflakeArctic is truly open, with an Apache 2.0 license, and all of our #data recipes and cook books.
.@SnowflakeDB is thrilled to announce #SnowflakeArctic: A state-of-the-art large language model uniquely designed to be the most open, enterprise-grade LLM on the market. This is a big step forward for open source LLMs. And it’s a big moment for Snowflake in our #AI journey as…
kinda wild that 21b flash shares same rank as Mistral large on LMsys.
🔥Newly updated scores for Reka Core, Flash and Edge on MMMU leaderboard: mmmu-benchmark.github.io.
Meanwhile on WildVision arena, Flash is #2, after GPT4-V. It's still early game (low votes) for now. but looks pretty promising! 😆
Good to see that on @lmsysorg, our feb version of Reka Flash 21B ⚡️from @RekaAILabs, despite only being 21B dense parameters has competitive performance to other much larger models like Mixtral 8x22 and Mistral medium 🚀🔥 We'll have much better Flash and Core soon! 🦾
its wild how gemini models represents two ends of the performance spectrum. gemini 1.0 pro: so nooby gemini 1.5 pro: so OP 🤯🤯🤯
@matthen2 It's a fun way to test out some different ideas too without having to wait around to see the results on 3D scenes.
@matthen2 It's a cool picture - here's my 352 splat parrot, I used generalized Gaussians e^(-x^4) to make it a bit more painting like!
So is @Rainmaker1973 still replying to me even though I’m blocked and I can’t see it ? If you would like to be blocked too, just suggest that the account stops stealing content. That seems to do it.
I don’t think they know what those words actually mean. Also, replying to tweets of people you’ve already blocked is crazy.
@matthen2 Wow this is insane. Is the jiggling at every split in the densification scheme a cause of high learning rates + momentum which shoot the gaussians like slingshots? I wonder if adapting the LR appropriately for the split gaussians could help
@matthen2 so siiick feels like there's a lot to explore here as a shader technique
@matthen2 this reader found the answer to be 16 (拾陆), 27 (贰拾柒) or oscillating between 24 and 25 (贰拾伍, 贰拾肆) in the case of Chinese numbers written in formal characters (壹, 贰, 参, 肆, 伍, 陆, 柒, 捌', 玖, 拾, 佰, 仟, 萬)
Hilarious first slide from @kscalelabs at AI Grant. 👏 Humanoid robots. Good for two things: 1) convincing smart people to work really hard 🤓 2) convincing investors to give you money 💰 Love the sense of humor😁
@matthen2 That does sound useful. I kinda want eg to have an entire doc site / blog in one file 😆
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