Ravisankar - Knowthyself @RKnowthyself

40 European AI startups that raised $50M+ in 2025. Most are hiring. From open-weight models to robotics, defence, quantum, and healthtech. 1/ @MistralAI 🇫🇷 – $1.7B open-weight models 2/ @HelsingAI 🇩🇪 – $600M defence & security AI 3/ @IsomorphicLabs 🇬🇧 – $600M AI for drug discovery 4/ @nscale 🇬🇧 – $433M full-stack AI cloud 5/ @neko 🇸🇪 – $260M AI health scanning 6/ @MultiverseQC 🇪🇸 – $218M quantum software 7/ @lovable 🇸🇪 – $200M AI product builder 8/ @quantumdrones 🇩🇪 – $181M AI drones for defence 9/ @n8n_io 🇩🇪 – $180M workflow automation 10/ @Quantexa 🇬🇧 – $175M decision intelligence 11/ @Xelix_AI 🇬🇧 – $160M AI for finance ops 12/ @cera_care 🇬🇧 – $150M digital healthcare 13/ @PhysicsxAI 🇬🇧 – $135M AI simulation software 14/ @NEURARobotics 🇩🇪 – $123M humanoid robotics 15/ @parloa_ai 🇩🇪 – $120M conversational AI 16/ @auterion 🇨🇭 – $105M drone operating system 17/ @ecorobotix 🇨🇭 – $105M precision agriculture AI 18/ @Keystone_edu 🇳🇴 – $104M recruitment AI 19/ @dexoryHQ 🇬🇧 – $100M warehouse robotics AI 20/ @framer 🇳🇱 – $100M AI web design tools 21/ @cusp_ai 🇬🇧 – $100M materials discovery AI 22/ Noxtua.com🇩🇪 – $91M sovereign legal AI 23/ @WeAreLegora 🇸🇪 – $80M collaborative legal AI 24/ Charmtx.com 🇬🇧 – $80M AI drug design 25/ @feedzai 🇵🇹 – $75M fraud prevention AI 26/ @LuminanceTech 🇬🇧 – $75M AI legal document review 27/ @tolokaai 🇨🇭 – $72M data annotation & labeling AI 28/ @nabla_ai 🇫🇷 – $70M AI healthcare co-pilot 29/ @AxeleraAI 🇳🇱 – $66M edge AI hardware 30/ DataCrunch Cloud 🇫🇮 – $64M AI compute cloud 31/ @comind_ 🇬🇧 – $60M neural interface AI 32/ @withbuena 🇩🇪 – $58M property management AI 33/ Hawk.ai 🇩🇪 – $56M anti-money laundering AI 34/ @DreamdataIO 🇩🇰 – $55M B2B attribution AI 35/ @ultromics 🇬🇧 – $55M AI cardiology diagnostics 36/ @73strings 🇫🇷 – $55M AI financial advisory 37/ Evoluteiq.com 🇬🇧 – $53M automation intelligence 38/ @attio 🇬🇧 – $52M AI-native CRM 39/ Tandemhealth.ai 🇸🇪 – $50M medical screening AI 40/ Omnea.co 🇬🇧 – $50M AI procurement orchestration 41/ @Quibimbiomarker 🇪🇸 – $50M AI radiomics and medical imaging

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There are many examples of those who have made it to the top, but you Sir, are the benchmark to teach us how to be, even after one has attained the summit. Thank you for all the love and support Sir. #1YearofBBVettaiyan @rajinikanth @LycaProductions

Statement from Kamal Haasan #Thuglife #ThuglifeFromJune5 #KamalHaasan #SilambarasanTR @ikamalhaasan #ManiRatnam @arrahman @SilambarasanTR_ #Mahendran @bagapath @trishtrashers @AishuL_ @AshokSelvan @abhiramiact @C_I_N_E_M_A_A #Nasser @manjrekarmahesh @TanikellaBharni #Vadivukkarasi #ChinniJayanth #vaiyapuri #Bagavathiperumal #Baburaj @alifazal9 @rohitssaraf @arjunchdmbrm #Chetan @rajshriartist #SrikanthMenon #NithyaShri @MShenbagamoort3 @RKFI @MadrasTalkies_ @RedGiantMovies_ @turmericmediaTM @APIfilms @homescreenent @actor_nithiin @SreshthMovies @PenMovies @GokulamMovies @5starsenthilk @dop007 @sreekar_prasad @anbariv @krutimahesh #SharmishtaRoy @amritharam2 @ekalakhani @AmbadyRanjith @AkihitoSculpt @Monesh_H @gopiprasannaa @magizhmandram @saregamasouth @saregamaglobal @NetflixIndia @Netflix_INSouth @idiamondbabu @prosathish @S2MediaOffl @UrsVamsiShekar @propratheesh @vaisakh_c_ @PROHarisarasu

‘தமிழ்’ உலகின் செம்மொழிகளில் இன்றும் பரிணமித்து வளரும் மிகத்தொன்மையான மொழியாகும். குறிப்பாக தமிழ் சங்கங்கள், ஆய்வுகள் மூலம் மொழியை வலுப்படுத்துவதிலும், அதில் திருத்தங்களைச் செய்வதன் மூலம் அதனைச் செறிவாக்குவதிலும் இன்றியமையா பங்கு வகித்துள்ளன. இப்படி புதுமை குன்றாத நம் தமிழின் நீட்சியை, அர்த்தமுள்ள தொடர்பாடல்கள் மூலம் அடுத்த தலைமுறையினருக்கு நாம் எடுத்துச் செல்ல வேண்டும் என்கிற பொறுப்பையே நமக்கு சுட்டிக் காட்டுகிறது. இந்த அடிப்படையில் ARR இம்மர்ஸிவ் என்டர்டெயின்மென்ட் குழு, தமிழ் மொழிக்கான ஒரு பெருமைச்சின்னத்தை உருவாக்கும் முயற்சியில் ஈடுபட்டுள்ளது, தமிழ் இலக்கியங்களை விளக்கப்படங்களாகவும் இன்னும் பல்வேறு புதிய வடிவங்களிலும் வழங்கவிருக்கிறது. ARR இம்மர்ஸிவ் என்டர்டெயின்மென்ட் குழு இந்த தமிழ் பெருமைச்சின்னத்தை ஒரு டிஜிட்டல் ரெண்டரிங்காக உருவாக்கவுள்ளது. எதிர்காலத்தில் இப்பெருமைச் சின்னத்திற்கென ஒரு கட்டிடமும் வரக்கூடும். இது குறித்து மேலும் தகவலகளை வெளியிடவிருக்கிறோம். இம்முயற்சி தமிழர்களாகிய நம் அனைவருக்கும் உற்சாகம் அளிக்கும் என்று நம்புகிறேன். தமிழால் மகிழ்வோம்! #thamizh #perumaichinnam

Colon cleansing is the most powerful yet ignored health intervention. It fixes chronic fatigue, skin problems, and weak immunity. I've tested this myself, and it does wonders. Here's how to perform a colon cleanse the right way: Check Thread 👇

We have to take the LLMs to school. When you open any textbook, you'll see three major types of information: 1. Background information / exposition. The meat of the textbook that explains concepts. As you attend over it, your brain is training on that data. This is equivalent to pretraining, where the model is reading the internet and accumulating background knowledge. 2. Worked problems with solutions. These are concrete examples of how an expert solves problems. They are demonstrations to be imitated. This is equivalent to supervised finetuning, where the model is finetuning on "ideal responses" for an Assistant, written by humans. 3. Practice problems. These are prompts to the student, usually without the solution, but always with the final answer. There are usually many, many of these at the end of each chapter. They are prompting the student to learn by trial & error - they have to try a bunch of stuff to get to the right answer. This is equivalent to reinforcement learning. We've subjected LLMs to a ton of 1 and 2, but 3 is a nascent, emerging frontier. When we're creating datasets for LLMs, it's no different from writing textbooks for them, with these 3 types of data. They have to read, and they have to practice.

DeepSeek lecture is edited and uploaded 👉 by-hand.ai/dpseek ~ Thank you all 🙏 for attending my public lecture yesterday. In one hour, I managed to build a simplified DeepSeek model in Excel in front of a live audience of 3000+ people.

My #reinforcementlearning Spring 2025 course at ASU starts tomorrow. Slides and videolectures to be posted on Fridays at the course website web.mit.edu/dimitrib/www/R… which also contains the 475 pp textbook and course material from past years' offerings

உலகெங்கும் வாழும் தமிழ் மக்களுக்கு என்னுடைய இனிய பொங்கல் வாழ்த்துகள்.

If you want the supramental Light, you must not tie yourself to mental ideas, but draw back from them and observe them with an impartial equality in the silence of the spirit. #SriAurobindo #IntegralYoga #Consciousness

🎉 Just finished the first version of the glossary for my free online e-book, Applied Machine Learning in Python! 💻📘 It’s been a lot of work, but totally worth it – thanks to the awesome feedback from UT students #Longhorns who asked for a glossary in my ML course. 🙏 The book features accessible, actionable education with downloadable workflows and links to my YouTube lectures. 🚀 Excited to share it with you all @ geostatsguy.github.io/MachineLearnin…∀! #MachineLearning #DataScience #OpenEducation

உலகின் பழமையான மொழியான தமிழ், ஃபிஜி நாட்டில் பிரபலமடைந்து வருவதைக் காணும்போது, அது நம்மை மிகவும் பெருமை கொள்ளச் செய்கிறது. #MannKiBaat

It’s been an amazing last couple of weeks, hope you enjoyed our end of year extravaganza as much as we did! Just some of the things we shipped: state-of-the-art image, video, and interactive world models (Imagen 3, Veo 2 & Genie 2); Gemini 2.0 Flash (a highly performant and efficient foundation model); Gemini-Exp-1206 model (top of the Chatbot Arena leaderboard); 2.0 Flash Thinking (our first ‘thinking’ model, expect a lot more news on this soon - as many of you remember, we pioneered this type of model with AlphaGo, AlphaZero, AlphaProof…); upgrades to @GeminiApp with Deep Research and more, fantastic new NotebookLM features, a new image remixing tool (Whisk); and a series of agentic research prototypes that can help people get things done (Project Astra, Mariner, Jules) all built on Gemini 2.0. And then on top of all of that, we dropped the world’s most accurate weather prediction model (GenCast), the world’s most advanced quantum chip that performed a computation that would have taken 10 septillion years (Willow - could come in handy for training AI one day!), and it was the honour of a lifetime to receive the Nobel Prize for AlphaFold, which has revolutionised structural biology and is being used by 2 million researchers around the world to understand disease and accelerate drug discovery. I could not be more proud of all the exceptionally talented teams at @GoogleDeepMind & @Google who have worked so incredibly hard on all these amazing projects. It’s the greatest joy one can have professionally to get to explore the outer reaches of science and human knowledge with such wonderful colleagues. We’ve been inventing the future of AI for well over a decade now, and we’ll continue to be a relentless engine of innovation. In many ways we’re only just getting started… if you want to be at the frontier of the most exciting scientific and technological journey ever, this is the place to be, come join us!

Only one thing is absolutely indispensable: the will to discover and to realise. #TheMother #IntegralYoga #Consciousness

”David Baker, Demis Hassabis and John Jumper, your ground-breaking work in computational protein design and protein structure prediction has revolutionised these fields. It has opened up completely new possibilities to design proteins that have never been seen before, and we now have access to predicted structures of all 200 million known proteins. These are truly great achievements.” Watch the very moment the chemistry laureates received their Nobel Prize diplomas and medals during the 2024 Nobel Prize award ceremony. #NobelPrize

Association of polygenic scores for neuropsychiatric traits with self-reported professions based on analysis of 420k individuals from UK Biobank and Million Veteran Program. Look at the 'arts & design' category. Artistic talent comes at a cost--a piece of your mind :) Voloudakis et al. Nat Hum Behav nature.com/articles/s4156…

Happy Birthday, dear Rajinikanth Sir! Your journey, both on and off the screen, continues to inspire us all. May you be blessed with good health, happiness, and endless moments of joy. Much love and respect. @rajinikanth

Long Live ❤️ #HappyBirthday @rajinikanth

Why are we doing this when our own country is so deeply in debt?

Department of Government Efficiency @DOGE

2 years ago

The United States gives more in aid to foreign countries than the next 9 countries combined. Where exactly is that money going and how is it being spent?

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The (true) story of development and inspiration behind the "attention" operator, the one in "Attention is All you Need" that introduced the Transformer. From personal email correspondence with the author @DBahdanau ~2 years ago, published here and now (with permission) following some fake news about how it was developed that circulated here over the last few days. Attention is a brilliant (data-dependent) weighted average operation. It is a form of global pooling, a reduction, communication. It is a way to aggregate relevant information from multiple nodes (tokens, image patches, or etc.). It is expressive, powerful, has plenty of parallelism, and is efficiently optimizable. Even the Multilayer Perceptron (MLP) can actually be almost re-written as Attention over data-indepedent weights (1st layer weights are the queries, 2nd layer weights are the values, the keys are just input, and softmax becomes elementwise, deleting the normalization). TLDR Attention is awesome and a *major* unlock in neural network architecture design. It's always been a little surprising to me that the paper "Attention is All You Need" gets ~100X more err ... attention... than the paper that actually introduced Attention ~3 years earlier, by Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio: "Neural Machine Translation by Jointly Learning to Align and Translate". As the name suggests, the core contribution of the Attention is All You Need paper that introduced the Transformer neural net is deleting everything *except* Attention, and basically just stacking it in a ResNet with MLPs (which can also be seen as ~attention per the above). But I do think the Transformer paper stands on its own because it adds many additional amazing ideas bundled up all together at once - positional encodings, scaled attention, multi-headed attention, the isotropic simple design, etc. And the Transformer has imo stuck around basically in its 2017 form to this day ~7 years later, with relatively few and minor modifications, maybe with the exception better positional encoding schemes (RoPE and friends). Anyway, pasting the full email below, which also hints at why this operation is called "attention" in the first place - it comes from attending to words of a source sentence while emitting the words of the translation in a sequential manner, and was introduced as a term late in the process by Yoshua Bengio in place of RNNSearch (thank god? :D). It's also interesting that the design was inspired by a human cognitive process/strategy, of attending back and forth over some data sequentially. Lastly the story is quite interesting from the perspective of nature of progress, with similar ideas and formulations "in the air", with a particular mentions to the work of Alex Graves (NMT) and Jason Weston (Memory Networks) around that time. Thank you for the story @DBahdanau !