Jorge Cortell

Sanctuary AI ranks 4th globally for patent holdings on general-purpose #robotics technology and dexterous manipulation technology, only behind NVIDIA, Alphabet and Hyundai. In this Bloomberg Tech Disruptors podcast, co-founder and CTPO, Olivia Norton, discusses how her company is leading the charge, despite being an emerging #startup in a field of tech giants. A great listen for anyone interested in learning how the future of #humanoid robotics is taking shape today! #ThriveVentureFund #FutureIsNow BDC BDC Capital (Canada)

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If you work in tech transfer this is a good read-in on how our diligence tech can assess and evaluate assets with minimal inputs. The best way to learn more is to see it live! Reach out to me directly to learn more!

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The proposed 5 levels of #Artificial #General #Intelligence #AGI #Chatbots: AI with conversational language #Reasoners: human-level problem-solving #Agents: systems that can take actions #Innovators: AI that can aid in invention #Organizations: AI that can do the work of an organization https://lnkd.in/gniqV-VQ

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Foundation models… “Many of these models are described as foundation models. This term, coined in 2021 by researchers at the Stanford Institute for Human-Centered Artificial Intelligence, broadly describes AI models that acquire the capacity to perform well across a range of different problems through a process of ‘pretraining’ on enormous unannotated datasets. This is in contrast to most machine and deep learning algorithms in the biology world, which are typically focused on very specific tasks.” https://lnkd.in/gZzDHFae

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On the surface, tech transfer operations (e.g. the process of transferring research and IP into commercialized opportunities) and early-stage startups may seem quite different. But when we at 9point8 Collective dug a little deeper, there was tons of overlap which speaks to the essence of zero-to-one development: 1️⃣ Innovation Focus: both tech transfer and early-stage startups aim to commercialize new technologies or solutions that can address real-world problems or create new opportunities. There is no blueprint to follow. 2️⃣ Intellectual Property: tech transfer ventures usually come with robust IP portfolios, including patents and trade secrets, and early-stage startups often focus on developing and protecting their IP to create a competitive advantage. Leverage IP as an asset is a key part of the strategy. 3️⃣ Market Potential: both tech transfer and early-stage startups target markets with high growth potential. They often aim to disrupt existing industries or create entirely new market segments, so targeting the right markets is essential. 4️⃣ Risk Profile: both types of ventures carry extreme risk and ambiguity due to the uncertainties associated with bringing new technologies or business models to market. With all this overlap, we innovated different versions of our diligence and assessment tool #VentureIQ to focus on tech transfer. Instead of a pitch deck as the raw inputs, we used patent filings instead. We wanted to see if our tech could generate credible insight on how raw technologies can be commercialized. The results have been pretty solid so far. From a single patent filing, we can extract technology readiness levels, target markets, competitors and benchmarks with similar technology, and even sources of public and private funding. From what our design partners have validated for us, these are monumental leaps in the development process -- saving thousands of dollars and weeks of time -- all done with #AI. Know of an interesting #techtransfer use case? Send me a DM so we can chat about it!

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This is just incredible. Neal Ghosh's demonstration of how #VentureIQ takes deeply technical and complicated content across a range of industrial use cases and ages/stages through an AI-generated conversational podcast (a la #notebookLM) is really mind-blowing. Check out his post, below, and if you haven't seen VentureIQ, yet, let's get you set up to learn more. You can visit VentureIQ.ai or DM any of us over here to book a demo!

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Excited for DCVC portfolio co Alta Resource Technologies to emerge from stealth! The design space of biology is many orders of magnitude larger than inorganic chemistry, and Alta uses it to massively reduce the cost of extracting rare earth metals. https://lnkd.in/g_q5UwRF

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When you don't check patents and IP details before investing in a startup

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Interesting to know #cloud #projectmanagement #projects #future #news #television #ai #artificialintelligence #technology #technologies #electronics #manager #managers #ceo #education #university #bigdata #datacenter #business #company #java #SQL #datascience #machinelearning #deaplearning #ki #deaplearning #azur #PTTglobal #PTTtechnology #excel #newyear #newyearresolution #ExcelTraining #DataAnalysis #PowerQuery #PowerPivot #ExcelMastery #2025Ready #ProfessionalDevelopment #charisma #leadershipdevelopment #executivecoaching #lifecoaching #highimpact #entrepreneurship #personaldevelopment #emotionalintelligence #softwareengineer #softwareengineers #django #samurai #irobot #nobel #connections

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https://lu.ma/gedw1srz event this upcoming Wed on embodied AI: come see robodog demos and hear Keith Adams , Jan Liphardt , Casey K. Caruso and more discuss where AI, robotics, and crypto intersect!

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A framework for human evaluation of large language models in healthcare derived from literature review With generative artificial intelligence (GenAI), particularly large language models (LLMs), continuing to make inroads in healthcare, assessing LLMs with human evaluations is essential to assuring safety and effectiveness. This study reviews existing literature on human evaluation methodologies for LLMs in healthcare across various medical specialties and addresses factors such as evaluation dimensions, sample types and sizes, selection, and recruitment of evaluators, frameworks and metrics, evaluation process, and statistical analysis type. Our literature review of 142 studies shows gaps in reliability, generalizability, and applicability of current human evaluation practices. To overcome such significant obstacles to healthcare LLM developments and deployments, we propose QUEST, a comprehensive and practical framework for human evaluation of LLMs covering three phases of workflow: Planning, Implementation and Adjudication, and Scoring and Review. QUEST is designed with five proposed evaluation principles: Quality of Information, Understanding and Reasoning, Expression Style and Persona, Safety and Harm, and Trust and Confidence. https://lnkd.in/giHmFEbA

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🚀Graphene technology breakthrough: What doors does it open for nanoelectronics innovation? A recent breakthrough at Tel Aviv University, where a team of researchers – including notable Israeli scientists – has developed a new method for growing graphene strips, may signal a seismic shift in semiconductor and quantum computing technologies. Graphene's potential has always been recognized, but its practical applications in nanoelectronics have faced significant challenges. We're looking at a future where carbon-based devices can be more efficiently integrated into existing technologies. The breakthrough involves a catalytic growth method that facilitates the growth of these narrow, long and structurally isolated graphene strips. This method has demonstrated record-breaking performance for quantum devices, showing that it's not only a theoretical advancement but also a practical leap forward. The intersection of academic research and venture capital investment in these emerging technologies is crucial.  At Tachles VC, we continue to be on the lookout for opportunities that align with these technological advancements, supporting startups that are set to redefine the tech landscape. More in the link below👇 https://lnkd.in/eufW6hQ7 #Graphene #QuantumComputing #VentureCapital #Technology #TachlesVC

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CRISPR-GPT: An LLM Agent for Automated Design of Gene-Editing Experiments abs: https://lnkd.in/dtK6E9mM "Introduces CRISPR-GPT, a tailor-made LLM agent for automated designing of gene-editing experiments. Focuses on breaking experiment design down to a variety of substeps that the agents solve: selection of the CRISPR system, design of guide RNA, prediction of off-target effects, selection of delivery system, etc. The agent was validated with human evals and even wet-lab experiments where 4 gene knockout experiments were designed with CRISPR-GPT with successful results."

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I could not agree more. I’ve had the pleasure of meeting Lamia Youseff, PhD, MSM a couple of times and I am always struck by her technical experience, but also her warmth,approachable style and her sage advice. Her insights mean a great deal for those of us at the Stanford University Graduate School of Business who are trying to get a foothold in the industry out here on the west coast. The takeaway for me was that to truly position yourself as an expert and strategic leader, we should focus on the problems that will arise once the current problems are solved, and to blend that with influence, passion and a high EQ. These are the keys to being a strategic leader.

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This Nobel Price for Physics to Professors Hopfield and Hinton has a special meaning for me. Their work had inspired my Master in Physics and the early years of my career as a Machine Learning scientist in the early ‘90s. There is an article in the Economist this week arguing that the Nobel committee had stretched this year the definition of physics to include computer science and artificial intelligence. I disagree. Despite the fact that the research of Hopfield and Hinton had a huge impact in computer science, the foundations and methods used by them are definitely in the field of physics. The Hopfield network was created with nodes and connections representing “spin glasses” a complex systems of material where spins of particles interact with each other. Very complex collective phenomena emerge from the study of these systems with applications in many fields, other than computer science. My Theoretical Physics Professor M. A. Virasoro at the University of Rome “La Sapienza” and his colleague in Rome, Professor G. Parisi, were leading world experts on spin glasses (Parisi received Nobel Price for Physics in 2021 also for his work on these complex systems). I first heard about neural networks from them in 1989 while at university and I decided to focus my research on this for my thesis. The same physics foundations can be found in the work by Hinton that is based on that from Hopfield where he applied the stochastic methods of statistical physics. His initial network was rightly named Boltzmann Machine because of the Boltzmann equation used. Hinton was the 1986 co-author of the famous Nature paper on the backpropagation algorithm that allowed training of a neural network with examples. He was also the co-author of the seminal work on Time Delay Neural Networks (TDNN) in 1989 by Professor Alexander Waibel, the first example of convolutional neural networks, still used in speech recognition today. For my thesis in 1990, I modified the architecture of TDNN improving their performance with a recurrent architecture that I named RTDNN. Hinton in 2006 revived neural networks from an apparent decline by introducing a method (using again Boltzmann machines) to pre-train complex neural networks with many layers of neurons. Deep Learning was born. So we should not forget that the theoretical foundations of Neural Networks are on physics and mathematics although the applications are now on many fields, computer science, particle physics, astrophysics, molecular biology, material science, economy, to name a few. #Nobel #Physics #NeuralNetworks

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Generative AI Breaking News (21AUG2024, Wednesday) - Rutgers University Cancer Research - GPT/Natural Language; Rutgers break's through using Generative AI for Cancer biologic protein sequence modelling. quote "Another category of AI-based tools for protein structure prediction are protein language models, which differ from AlphaFold2 and RoseTTAFold in that they are not trained on structures but rather on protein sequences7,8,9. Collectively, such protein structure prediction tools have been extensively used by researchers across various disciplines in the biological sciences and are expected to continue to add value alongside experimental structure" end-quote #rutgers, #cancer, #oncology, #pharma, #biotech, #machinelearning, #startups, #newjersey, #jersey, #miami, #geneva, #switzerland, #lifesciences, #investments, #israel, #berlin, #hedgefunds, #privateequity, #stocks, #nasdaq Ref - https://lnkd.in/eR2RYzvv

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NeuroXess’ new BCI, implanted into an epileptic patient’s brain, could not only decipher the complex Chinese language but also operate a robotic arm and interact with AI. NeuroXess reports that BCI achieved 71% speech decoding accuracy using 142 common Chinese syllables within five days, with a single-character decoding latency of under 100 milliseconds. This is the highest level of real-time decoding of Chinese speech that has been achieved in China to date.

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