Wee Hyong T.

There’s huge interest in securing #LLMs and #GenerativeAI, and quite a crowd at Ravi Ithal’s session at #RSAC2024: A Step-by-Step Guide to Securing Large Language Models. Insight: LLMs are equivalent to humans in the OSI model (i.e. one layer up from the application layer). Their data should be secured via #DSPM (scanning for data at rest, on-demand APIs for inputs), and their semantics (do inputs and outputs comply with company policy, e.g. are queries appropriate to the intended use case) should be secured via #LLMs. Securing the semantics is in its infancy.

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OpenAI is undergoing significant restructuring and internal changes related to status and sparking an exodus of high-profile executives. #datascience #AI #artificialintelligence https://hubs.li/Q02ShsZy0 If you enjoyed this post, follow me for more insights on AI and data science!

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In a world full of LLMs Google DeepMind quietly releases a new version of AlphaFold, a model that predicts structure and interactions of all life’s molecules (proteins, DNA, RNA, ligands) with unprecedented accuracy. For the interactions of proteins with other molecule types we see at least a 50% improvement compared with existing prediction methods. https://lnkd.in/dJkNghUY

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The 2024 edition of the Stanford AI Index is out, and highlights PaLM-E and RT-2 as this past year's research spotlights in robotics: https://lnkd.in/gemZZzXJ

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It has been my view for the last few months that the next big change in LLMs will be algorthmic optimization. Now comes this article. Don't sell your nvidia stock just yet, but remember that LxM technology is not just GPUs. https://lnkd.in/gyifxnHd

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OFAI aims to enhance our understanding of AI and its potential to augment human capabilities while promoting responsible development practices.

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In this #ILTACON204 session, Relativity's Avani Gossai reminded us of Uncle Ben's wise words, weaving a web of wisdom on the power and responsibility of generative AI 🕸️. Joined by Harbor's Julie Strachan Haiber, BakerHostetler's Priti Saraswat, CIPP/US, and WordRake's Ivy Grey, the panel spun a tale of #legaltech heroics, emphasizing the importance of safeguarding data privacy 🛡️ amidst the growth of AI. 

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Next month, I'll be in Boston to keynote MIT Technology Review's Future Compute event. The focus of my talk will be on the #future of human-computer interaction, the expansion of computing into the physical world, vision-enabled #AI, and the evolution of the web. My talk will center around #SpatialComputing – Temporary or Transformative "For some, Spatial Computing is a passing fad, but those closest to the technology posit that what we know about computing is about to shift, significantly. Spatial Computing is an evolving 3D-centric form of computing that uses AI, computer vision, and XR to blend virtual experiences into the physical world. From a business perspective, it expands computing into everything you can see, touch, and know. Attend to decide whether Spatial Computing is a passing trend or a lasting transformation in computing." You can join in person or online. #Future #Compute, MIT Technology Review's one-day digital leadership forum to be hosted before EmTech Digital on the MIT campus. It will gather business leaders exploring impactful emerging technologies and strategies that will drive transformational change. #FutureCompute #tech #business #AI #spatialcomputing #gaming #Genalpha #visionenabledAI #AIwearables #software #hardware #EmTechDigital (Link to register in the comments)

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Embrace AI Responsibility: George Chamoun shares insights into the evolving landscape of AI solutions. Dive into the essential aspects that go beyond predictive performance and contribute to building responsible AI systems. 👉 https://lnkd.in/giiBCksk #responsibleAI #AIsolutions #aitools #ai

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What is #AmazonBedrock? This new fully managed service offers a choice of high-performing foundation models (FMs) from leading AI companies and Amazon through a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI. Since Amazon Bedrock is serverless, you don't have to manage any infrastructure, and you can securely integrate and deploy generative AI capabilities into your applications using the #AWS services you are already familiar with. Find out more ⬇⬇ https://lnkd.in/d4NTvgR6 Simon Johnson, Peter Vorley, Lawrence McEwen

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The keynotes for #ODSCWest 2024 represent the best in the field of AI, featuring experts from UC Berkeley, NVIDIA, Anthropic, Voltron Data, MIT, and Google Cloud. #datascience #AI #artificialintelligence https://hubs.li/Q02ShsR50 If you enjoyed this post, follow me for more insights on AI and data science!

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Eric Topol, MD interviews Kate Crawford, professor at both USC and Microsoft Research and leading scholar of the social implications of #AI as they attempt to answer the question: What are the costs #generativeAI is incurring on the planet, and also on us as a people? Some prominent ethical questions the interview raises that I found particularly disconcerting: 🙋‍♀️ What sorts of biases are hidden in AI models and how will they be propagated if we start to use AI for healthcare, education or even criminal justice decisions? 🙋‍♀️ Who are the humans doing the hard work of labelling material while being paid less than $2/hour to generate a training model? 🙋‍♀️ How can we create a system that will continue to reward artists, writers and musicians for the hard work they do when some of their work can also be ingested by AI and reproduced in a way that is not copyrighted? #AIethics is not just about how #generativeAI is being used and how to create policy to govern its use, but also what the hidden costs are of continuing to invest in it as a technology 🌎 I'm encouraged to know that researchers like Kate Crawford are looking into how these systems are being built, who might be harmed and how we can mitigate the risks that come with this big shift towards #AI. #AIethics #ethicsinTech #AIRegulation https://lnkd.in/e_62ZetE

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101 real-world gen AI use cases featured at Google Cloud Next ’24 by @google snapshot of how 101 of these industry leaders are putting AI into production today, creating real-world profitable use cases! #rafAIgual #GenAI #usecases #enterprise #adoption

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Check out a paper being presented at the GenAI workshop at @chi2024 tomorrow where Larry Birnbaum and I explore how GPT can help with analytical narrative structure. https://lnkd.in/gxiF6MU7

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Amazon's Alexa is set to receive a significant AI upgrade, potentially powered by Claude, which could bring us closer to truly smart speakers. This enhancement aims to make Alexa more intuitive, responsive, and capable of understanding complex queries with greater accuracy. By integrating advanced AI technologies, Alexa could evolve from a simple voice assistant into a more intelligent companion that anticipates user needs and offers more personalized experiences. As AI continues to advance, innovations like this are transforming how we interact with technology in our daily lives, making smart speakers an even more essential part of our connected homes. Read more from Tech Radar here => https://tulle.cc/mo7 #AI #SmartSpeakers #Alexa #Innovation #TechTrends

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Large language models can be applied to all kinds of data, not just natural language and code. In this post co-written by Hugging Face and Intel AI, we'll will show you how to work with the state-of-the-art ProtST protein language model, and how the Intel Corporation Gaudi 2 accelerator does a nice job at accelerating inference and fine-tuning versus NVIDIA GPUs 😀 https://lnkd.in/eCGcqRfF #ai #opensource

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AI like Chat-GPT, Copilot and Gemini are all poised to streamline tasks and build a new age of creativity. But how do they all manage to create content? By leveraging Large Language Models. LLMs are neural network computing models designed to analyze a request and build a response in a way similar to how the human brain would. Some use cases include: — Analyzing and summarizing large amounts of information — Assisting in customer support tasks — Understanding spoken words and completing administrative tasks — Reviewing patterns in data to prevent fraud and hacks. Safety Mojo, our AI-powered safety platform, leverages LLMs to streamline safety forms and provide detailed information on worksite plans and procedures. Want to learn more about LLMs and Safety Mojo? Visit our blog today: https://lnkd.in/gXpzyzCn #AI #NeuralNetworks #LargeLanguageModels #MachineLearning #SafetyMojo

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