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Jing Xie
I usually post about genomics, but several Heads of Cloud at hedge funds have reached out to talk about spot instances & checkpointing: 1. They want to either save the firm money or reallocate that money to other initiatives like ML / GPU experimentation to make more money for the firm 2. Cloud enables engineering teams to scale compute up or down better than fixed-size datacenters (which have large CapEx commits) 3. They are using Spot instances to save on costs 4. Longer spot reclaim notification windows are valuable and make a difference: AWS has the longest notification window (2 mins) Azure and GCP run on a 30 sec default, but more time can be negotiated 5. Building high quality apps for internal end-users is important, but spot reclaims frequently delay P&L simulation, scenario modeling, and other analyses that are necessary for the next trading day 6. Using spot instances for long-running simulations and complex trading scenarios is very challenging as there is little trust that jobs will safely finish on time 7. Job submission systems ask end-users to key in compute resource requirements such as number of cores and GB of memory But they don’t always know what they need when performing Macro or Event-Driven or Vol-Spike related research. This can be problematic because you’re either wasting compute by overprovisioning or risking job failure by under-provisioning. 8. Horizontal cloud auto-scaling architectures don’t account for increasing rates of Spot reclaim. These reclaims can occur for particular regions during busy periods and kubernetes architectures are not great at protecting against large numbers of Spot reclaims. Do these sound familiar to you? If so, I’d love to learn more. Shoot me a DM or leave a comment with your thoughts. #hedgefunds #HPC #CloudComputing #researchplatform
112 Comments -
Morgan Cheatham
Open-source models can be a strong lever for increasing gross margins at AI companies, especially those that have hefty cost structures (e.g., enterprise sales orgs that require significant customer success or implementation resources, as well forward-deployed AI services models common in healthcare and life sciences). One of many reasons to maintain a modular and flexible stack with minimal dependencies when building an AI company. More on the importance of flexibility in the AI stack: https://lnkd.in/eA2XATRk h/t Delip Rao #ai #artificialintelligence #generativeai #healthcare
506 Comments -
Diogo Camacho
“The AI Playbook” by Eric Siegel. If you’re a business leader working in the ML space: read it. If you are a data scientist, broadly defined: read it. If you are strategy and ops: read it. There is more to ML than saying “we do x with ML”. Ties back to starting with why à lá Simon Sinek and how to build effective organizations as Stephanie Wisner highlights. The term bizML will take time to sink in, but it’s an interesting concept. Thank you for making me put the book top of list, Eric Sigel! #machinelearning #datascience #biotech
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Asif Razzaq
OpenPipe Introduces a New Family of ‘Mixture of Agents’ MoA Models Optimized for Generating Synthetic Training Data: Outperform GPT-4 at 1/25th the Cost Quick read: https://lnkd.in/gfxdiDT5 OpenPipe’s MoA models have excelled in rigorous benchmarking tests, achieving notable scores on LMSYS’s Arena Hard Auto and AlpacaEval 2.0. The MoA model scored 84.8 on Arena Hard Auto and 68.4 on AlpacaEval 2.0, indicating its superior performance in generating high-quality synthetic data. These benchmarks are critical as they represent challenging user queries that test the robustness and adaptability of AI models. The MoA model has been benchmarked against various GPT-4 variants in real-world scenarios. Results showed that OpenPipe’s MoA model was preferred over GPT-4 in 59.5% of the tasks evaluated by Claude 3 Opus. This is a significant achievement, highlighting the model’s effectiveness and practical applicability in diverse tasks encountered by OpenPipe’s customers...... OpenPipe
433 Comments -
David Armano
The LLM will see you now: Google and DeepMind released a paper on Monday describing Med-Gemini, a group of advanced AI models targeting healthcare applications. The authors claim that Med-Gemini is outperforming competing models such as OpenAI’s GPT-4. During the pandemic we saw the rise of Telehealth which has largely come back to earth but could doctors be consulting more often with AI? (We know they already Google stuff) #Healthcare #AI
129 Comments -
Ari Hershowitz
In just a couple of days, thanks to the work of Osma Suominen (and the Annif tool - suggested by Juho Inkinen), there are some very compelling results (> 0.95 recall for policy area, and F1 of nearly 0.74 for subject areas), demonstrating the power of open data on Hugging Face and the excellent international Library community! In follow-up discussions with Marci Harris and Leonard Park, my team at DreamProIT plans to add Committee referrals to the data set. This could allow a model to recommend committees, based on prior bill referrals... See https://lnkd.in/gww39QeG
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Swarbhanu Chatterjee
An AI tool, AlphaFold 3, for drug and vaccine discovery, that simplifies modeling how proteins fold, allowing for easier targeting at the molecular level. You upload the protein sequence to the server and 10 minutes later, you’ve got the shape and the structures. Something that would take years to do otherwise. This is not Gen-AI, but it is as useful or maybe more. AlphaFold3 is limited to non-commercial use through a DeepMind website. The Nature publication's url is in the post.
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Pankaj Mishra, PhD
Lately, I've been experimenting and building data pipelines for Future Therapeutics and realized how little we talk about data pipelines in cheminformatics. It's a domain where, at any given time, we handle large volumes of data from multiple sources. I'm sharing a special collection of articles on Cheminformatics Data Pipelining, designed to raise awareness and enhance skills in this critical area. Part 1 of 8 is published. Have a look and feel free to share your feedback. Also, let me know if I miss something specific for cheminformatics. I would also love to talk to those actively involved in data pipelining projects to hear your thoughts and approaches. #cheminformatics #drugdiscovery #datapipelines https://lnkd.in/gDa7G2_z
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Chris Gonzales
Summary: A generative AI startup, Triomics, claims it can significantly reduce the time it takes for doctors to match cancer patients with clinical trials. They have developed a platform that uses AI and LLMs to extract data from electronic health records and help doctors find suitable trials for patients in minutes instead of hours. Key takeaways: Only 3% to 5% of eligible cancer patients enroll in clinical trials due to the time-consuming process of manually reviewing medical records. Triomics has already partnered with six cancer centers and hospitals and plans to double that number by the end of the year. Triomics' platform, OncoLLM, has multiple use cases beyond clinical trial matching, including helping prepare for patient visits and submitting cancer data to regulatory agencies. Counter arguments: Other AI startups, such as Deep 6 AI and QuantHealth, are also working on clinical trial matching, posing competition for Triomics. While Triomics is specifically focused on cancer centers, other startups like Trajectory are using AI for clinical trial matching in a broader range of medical specialties. #fundraising #startups #vc
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(Michael) Sebastian Metti
I spoke today with computational bio expert Jefferson Parker, PhD (at NullSet Informatics Solutions) for our State of AI in Biotech report. He shared some interesting career advice for those working in AI: 9 out of 10 leaders in biotech want AI in their scientific development, but do not know WHY. 1 out of 10 DO know why. They probably have the best data, and that is a blessed place to be and develop in your career. Always ask why leaders want AI and much more will be revealed. And for leaders, understanding why you want AI (beyond the hype and promises) will lead to a team culture that prioritizes data and let's the best talent flourish. It's win-win.
243 Comments -
Ben Cappellacci
Lately I've been curious to learn more about how AI is impacting biology and drug development. With all of the hype around Generative AI for text, there seems to be a growing discussion around Causal AI to identify new proteins and predict treatment outcomes. I thought I'd share a few helpful things I've read in the area: This article from Century of Bio offers a great explanation of how causal AI is used for protein discovery. It also gives a really approachable breakdown of how this kind of AI works. https://lnkd.in/g3U3fA4D This article from Nature Medicine goes into detail around the benefits of causal AI for predicting medical outcomes and how it can lead to better individual patient predictions: https://lnkd.in/ggnsvD4z This paper looks at the early success of AI developed drugs in the place where it matters most: clinical trials. It's interesting to see that the early pipeline of drugs designed using AI are in line with historical averages for classically developed drugs (around 40%) https://lnkd.in/g3Y6Jf5S I'll be keeping a close eye on this space! #ML #AI #CausalAI #Biology
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Madan Ram
Check out our latest post on Clappy.ai, "Leverage Layout-Aware RAG for More Accurate Retrieval of Knowledge from Documents." Discover how to harness the power of Retrieval-Augmented Generation (RAG) for documents in PDF, Doc, and Markdown formats. Dive into the specifics of implementation and explore our reference repository to get started with advanced RAG for your knowledge base. Don't miss out on this essential read! Continue reading here for all the details: The Power of Hierarchical Indexing with RAG. (https://lnkd.in/gbiVHfcH)
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Bernardo Perobeli
Anthropic has launched Claude 3.5 Sonnet, the inaugural release in their upcoming Claude 3.5 model family. This new AI model sets unprecedented industry benchmarks for intelligence, outperforming competitor models and even Anthropic's own Claude 3 Opus across a wide range of evaluations, including graduate-level reasoning, undergraduate-level knowledge, and coding proficiency. Claude 3.5 Sonnet demonstrates significant improvements in understanding nuance, humor, and complex instructions, while excelling at producing high-quality content with a natural, relatable tone. ➜ Check the news at: https://lnkd.in/dbKMKPm7 ➜ Vendorvise's official Instagram: https://lnkd.in/ebK2KQ2C ➜ Vendorvise's Linktree: https://lnkd.in/dQdbMdth 🤖 If you enjoy reading my posts about AI and tech news, hit that like button and share with your friends to support my content! #ai #artificialintelligence #ainews #aipowered #news #blog #claude3 #sonnet #anthropic #generativeai #llms #tokens #aitools #aitech #tech #technology #hardware #content #socialmedia #future #new #launch #business #techtrends #innovation #success #markets #people #industry
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Brent Zettel
#hiring If anyone knows an awesome engineer that would be interested in joining an emerging #AI company doing important work in #healthcare, please drop me a line! Andy AI is backed by General Catalyst, YCombinator, Greater Ventures, and others, and they’re looking to hire a full stack engineer (US based) who's excited about using AI to improve healthcare and reduce nurse burnout. Andy is AI software that automates clinical documentation for nurses who do home visits. A nurse makes an audio recording of the visit and Andy automatically generates a form that usually takes nurses 90 minutes to complete. Nurses love the product because it potentially saves them 15 hours of charting a week! The founders previously built healthcare AI at Google Health and Apple, and are now building their vision to transform home health. More about Andy AI: https://with-andy.com/ Nurses love it: https://lnkd.in/g9XqZrUq #GenAI #digitalhealth #hiring #engineers #healthtech
142 Comments -
Trevor Mason
Dan Primack had some pointed criticism for #VC yesterday in his Axios Pro Rata newsletter (a daily must read IMO 😤). In short, the model doesn't work if it can't produce exits for LPs. Don't blame public markets (which are at all-time highs) for the lack of liquidity either. 📈 💸 Instead, this is a "liquidity drought of your making" where "...swinging for the fences on every pitch, rather than taking the single or double that's available" is the only way out when you invest at "sky high valuations." 😰 "A whopping 37% of "unicorns" are being held for at least nine years by VC funds, including 13% that are past the 12-year mark." 😳 ⌛ Is he right? Is VC at a dire inflection point? Or is Primack prematurely hitting the panic button? 🚨 https://lnkd.in/dts92pXr
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Brian Laung Aoaeh, CFA
#ObsessivelyEnthusiasticInvestor #UnreasonablyEnthusiasticInvestor #IrrationallyEnthusiasticInvestor at REFASHIOND Ventures: The Industrial Transformation Fund. We look for the people we believe are doing the best work in Industrial Transformation & Supply Chain Technology; Attempting the impossible. Then we go all-in on them. With obsessive and unreasonable enthusiasm. Join us. #IndustrialTransformation #SupplyChain #Innovation #Technology #Startups #VentureCapital #DemandTheImpossible #UnreasonableEnthusiasm #ObsessiveEnthusiasm #IrrationalEnthusiasm
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Brian Nichols
Excerpt from an Angel Squad memo that we invested in recently: “[Company] is led by a team of scientists and engineers with PhD-level expertise in Machine Learning, Engineering Simulations, and Computational Materials Science. The team is headed by CEO, [Name], who previously led AI development at two early-stage startups. [Name] is joined by CTO, [Name], who has deep experience in machine learning and materials science, and Chief Science Officer, [Name], a doctoral researcher at the [School]. “ Investing at the earliest stages of value creation often means taking big bets on a founding team. At Angel Squad and Hustle Fund, we love founders with deep expertise and super domain knowledge, particularly in deep tech verticals.
283 Comments -
Ben Guo
For NY Tech Week we'll be demo-ing Substrate at the South Park Commons Science Faire on Thursday: https://lnkd.in/e5JwDKKX There are so many incubator-shaped things out there these days, but there's nothing quite like SPC. It's like a chill, small-batch, locally-sourced alternative to YC, where you can either hang out as a member forever - or choose the VC-funded adventure. The -1 to 0 phase [0] they talk about at SPC is real, and it made a real difference for us to have a home at SPC. It takes a lot to quit your job and do something new, especially when it isn't entirely clear what you're doing. (1) Do it – take the leap! and (2) consider joining SPC. Though the core vision has remained the same, many of the important turns in our squiggle at Substrate (including the graph framework) came from those early days at SPC. If you're here for tech week and can't catch us at SPC on Thursday, DM me if you want to meet up! [0] https://lnkd.in/e6KEMr9V
331 Comment -
Akash Sharma
💥 New day, new model 💥 We ran our performance benchmarks on Anthropic Claude 3.5 Sonnet v/s OpenAI's GPT-4o & the results weren't what you'd expect ⏬ Anthropic says Claude 3.5 Sonnet outperforms all competitor models on key evaluations, at twice the speed of Claude 3 Opus and one-fifth the cost. In our benchmarks 3.5 Sonnet & 4o came out neck & neck. Ultimately, you need to run evaluations on your task at hand and measure the quality yourself. 🔍 Data Extraction: Both models identified 60-80% of data correctly, but neither excelled in this task. 📊 Classification: Claude 3.5 Sonnet (72%) outperformed GPT-4o (65%) in mean accuracy. However, GPT-4o led in precision (86.21%), crucial for accurately classifying customer tickets. 🧠 Verbal Reasoning: GPT-4o outperformed Claude 3.5 Sonnet with 69% accuracy, versus 44%. Both models did well on analogy and relationship questions. 📜 Context window: Claude 3.5 Sonnet boasts a larger context window (200K) compared to GPT-4o's 128K 🌪 Latency: Claude 3.5 Sonnet is 2x faster than Claude 3 Opus, but it’s still lags behind GPT-4o when it comes to latency (50% faster Time to First Token) Price and throughput for these models was very similar Want to learn more about how these models stack up? Check out our full analysis on the Vellum blog: https://lnkd.in/dwEcQJe4 Oh and did I say, Claude 3.5 Sonnet is already in Vellum? Sign up for a demo to run your evals & start building!
671 Comment -
Druce Vertes
AI Reading for Sunday May 12! Speculating about OpenAI's Monday announcement. https://lnkd.in/e4nA2xKd More rumors of what ChatGPT might show. - THE DECODER Top guesses according to Perplexity, others, and yours truly - Project Q* which possibly learns to solve complex multi-step reasoning problems with something like Q-learning and tree search. - Something with agents and improvements to Assistants API which Sam Altman has been hyping - Better voice assistant - Not GPT-5 per Sam Altman, but maybe 4.5 with a long context and multimodality to catch up to Google, and price reductions for GPT-4 matching cheaper startups - Improved AI studio dev tools. - Maybe OpenAI should release a small local open source model and runtime environment for finetuning it. That space is buzzing but the technical bar to get into it is high for most people. Or maybe, a sarcasm detector. Wow, a true leap for mankind. Great job, Einsteins. - PCMAG OpenAI removed 'our most advanced' from the description of GPT-4 ... a more advanced 4.5 or something coming? Either they have poor opsec or are good at getting attention with headfakery. - Reddit ARM to launch AI chips to compete with Nvidia. But their business model is they don't sell chips, they license designs to vendors like Apple and Amazon and Nvidia, so this is new for them. ARM might have pricing power and a roadmap to capture more of the value chain, also might push customers to e.g. RISC-V. - Nikkei Asia WSJ covers NYC AI startups in NYC like HuggingFace, Runway, Pinecone, which are raising money at 1/2 the pace of Bay Area - WSJ Pro Alibaba leverages cloud business to become leading AI startup investor in China. - FT Wikipedia adds an LLM-powered Chrome extension for fact-checking. - Chrome Store How did that robot commencement speaker work out? Looks kinda weird and creepy. - YouTube Researchers test AI systems' ability to solve the New York Times' connections puzzle Tesla exec leaves, suggests it's a toxic work environment and "The recent layoffs that are rocking the company and its morale have thrown this harmony out of balance and it's hard to see the long-game." - Futurism Videos of cheerleaders engaging in off-limits activities were circulated. The cheerleaders and cops said they were deepfakes. A woman was accused of deepfaking them. Not deepfakes, although possibly underhanded shenanigans of unclear motivation. - the Guardian
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