Vassil Dimitrov

We have figured out a lot using mathematics, physics and chemistry to understand nature. We know how to predict electron flow in semiconductors, fluids in tubes, clouds in the sky, airflow over wings, space storms etc. Tools like computational fluid dynamics have remarkable applications in unexpected places. We also have ideas around PINN and we can use those insights to help us understand what happens in a foundational model. And I am sure there are lots more. None of these software artifacts should ever be said to be un-knowable or a "blackbox". That's intellectual laziness. These are all man made structures. We've figured out many parts of nature using math, physics and chemistry - we've mapped the Human Genome, so what's the excuse in not understanding foundational models? I look forward to people recognizing that there are existing human inventions (math, physics etc) whose insights can be used to remove/reduce the probabilistic nature of foundational models and thereby benefiting humanity as a whole. A press conference was held by University of Toronto with Geoffrey Hinton after the announcement that he was one of the two recipients of this year's Nobel Prize for Physics. Geoffrey is probably the only Turing Award winner to also have won a Nobel Prize. And the video - https://lnkd.in/gVHewNCd. Geoffrey is spot on where he says, at about 3:38: "I'm particularly proud of the fact that one of my students fired Sam Altman." Brilliant! #nobelprize #ai #opensource #turingaward

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This is so exciting. For the Nobel body, for the scientific community, and for the world to acknowledge the tremendous work done to enable AI and ML as we know it today. The shift in paradigm that was created with Jeffrey's work (and the co-recipient's) has made work in this space, deep, philosophical and applicable at same time. https://lnkd.in/ggW-q45K #machinelearning #ai #artificialintelligence Congratulations form all of us at Mesh AI (collaborative scheduling to end clinician burnout).

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🔬 Researchers from Lawrence Berkeley National Laboratory (Berkeley Lab), UC Berkeley, the Institute for Systems Biology, and Université Laval have unlocked new insights into the TIP60 protein complex, a critical gateway to DNA accessibility. Published in the journal Science, this groundbreaking study reveals the atomic structure of TIP60, paving the way for potential breakthroughs in targeted therapies for diseases such as cancer and Alzheimer's. Using advanced high-resolution cryo-electron microscopy, the team elucidated how this complex enables essential DNA repair and transcription processes, which are vital for cellular health and often disrupted in disease states. This research not only enhances our understanding of genetic regulation but also opens exciting avenues for developing therapies that manipulate TIP60's activity to treat genetic and neurodegenerative disorders. Explore how this significant discovery could transform future medical treatments! #Genetics #HealthcareInnovation #ScienceNews Read more: https://lnkd.in/eMnjr2bp

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Dr. Tali Dekel, a leading researcher in generative AI from the Weizmann Institute of Science, is pushing the boundaries of what's possible with large-scale deep-learning models! Her collaboration with Google has led to the creation of Lumiere, a groundbreaking text-to-video model for video generation. 🌟 Lumiere can transform simple text prompts or reference photos into rich, realistic videos. Imagine a squirrel on the Moon or a yawning Mona Lisa – Lumiere makes it happen! Dr. Dekel's work focuses on "re-rendering reality," recreating the visual world using computational tools. Her team's research is revealing fascinating insights and pushing the frontiers of technology! https://lnkd.in/eYKQYzKm #AI #WomenforScience

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I recently interviewed Lisa Lambert, CEO of Quantum Industry Canada (QIC), on the state of quantum technologies in Canada. We covered a lot of ground, starting from a general overview of quantum, the roles that Lisa and QIC play in the ecosystem, the history of quantum development in Canada, the current state of play, and what needs to happen from here. My goal was to be able to answer two questions: 1 - How did Canada become a global leader in quantum technology?  2 - Can we generalize that path to other sectors of deep tech? If you did not see it yesterday, I suggest you start with the full article at link [1] in the comments, or the previous post at [2]. As Lisa noted, quantum leadership in Canada was seeded by a series of investments starting with Mike Lazaridis and the founding of the Perimeter Institute. While investment was massive for an individual, it was small relative to the amounts that are being poured into AI today. Canada’s budget 2024 has allocated $2.4B for AI infrastructure investments [3], less than half of what OpenAI is projected to spend by itself. While this is nearly an order of magnitude more than amount that founded Perimeter, the decades-long delay in committing relative to the same point in quantum development means that Canada’s AI investments will barely move the needle globally. Where quantum technologies got support in the very early stages of development, Canada may have missed its opportunity in AI due to underinvestment in the early stages. While giants like China can afford to come late to the party by simply throwing vast resources at the problem, we cannot. Investing early means that a much smaller investment is needed to achieve impact. If Canada hopes to benefit from its research excellence across all deep tech sectors, the public sector needs to embrace risk and invest in technologies when they are still in their nascent stages. Finally, we need to stay the course. While Canada leads in quantum technologies for now, the hard work of QIC and other private sector supports for early commercialization efforts of quantum and quantum-enabling technologies remains essential in carrying Canada across the finish line. From the recent policy-induced whiplash relating to procurement cuts [4], delays to the CIC [5], and Canada’s underinvestment relative to China, the Netherlands, and even Singapore [6-8], it is likely that without this hard work, our public sector innovation leaders would drop this ball, too. The challenge is also an opportunity. While AI may have been missed, the productivity of our national research machine means that technologies abound that could be the next disruptor. The last few decades of quantum technologies provide a clear blueprint for how to achieve deep tech dominance that can be readily replicated in other sectors. Thanks again to Lisa for sharing her insights, and to QIC for the work they continue to do in pushing Canada’s quantum sector forward.

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🚨  Unlocking Lithium Secrets: AI Cracks the Code on Quebec's Geological Data 🚨 James Bay Minerals' recent discovery of Li-rich green crystals (4000+ ppm) in a #pegmatite outcrop highlights the untapped potential of #Quebec's Eeyou Istchee-James Bay district. 🗺️ Strategic Location: - Along-trend from Patriot Battery Metals Corvette deposit (109.2Mt @ 1.42% Li2O) - Near Sayona Moblan and Winsome Resources Ltd's Sirmac-Clappier projects 💡 Unlocking Historical Data: Quebec's 160+ years of exploration history is buried in 5M+ pages of multilingual reports (Ministère des Ressources naturelles et des Forêts (MRNF) SIGEOM EXAMINE). How do we efficiently identify similar Li-bearing pegmatites? 🚀 Enter RadiXplore GeoAI 🚀 Powered by advanced #AI, RadiXplore processes these vast historical records, making it easy to analyze them in a geologically meaningful way. We recently tested it in the Eeyou Istchee-James Bay district, searching for pegmatites with green crystals ("pegmatite avec cristaux verts") and generated a heatmap of the results. The platform handled this #multilingual repository with ease, pinpointing every potential lithium-bearing pegmatite in the area. We've even validated these results by diving into one of the reports—spot on! 👀 See It In Action: The image shows a heatmap of "pegmatites with green crystals" across the region, with each hotspot representing potential Li mineralization. 🔬 Validated Results: We've included a sample report to showcase RadiXplore's accuracy in multilingual analysis. ✔ Ready to supercharge your exploration efforts? Whether you want to test-drive RadiXplore on Quebec's SIGEOM database or enhance your proprietary datasets, let's connect! #lithium #exploration #geospatial #AI #geospatialAI #Quebec #Canada #minerals #batterymetals #greenenergy #innovation #radixploreusecase #radixploremining

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Quantum science will change the world. This is no exaggeration – it is happening. But where it will happen remains an open question. One thing, however, is clear: It will be where leaders make it a priority. Good things happen to those who commit. Canada, among other countries, has taken the first steps in this direction, but seeing it to fruition will be a big challenge. In an article from the forthcoming edition of the Innovation News Network Innovation Platform, Paul Smith, Perimeter Institute for Theoretical Physics Managing Director and Chief Operating Officer asks what it will take to bring the long-promised quantum technology revolution to fruition. Read the whole article here: https://lnkd.in/eGaHg-Ke #canada #horizoneurope #quantum #quantumphysics #quantumcomputing #quantumtechnology #science #research

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Today’s Nobel Prize in Physics Congratulations to Geoffrey Hinton for being a co-recipient of the 2024 Nobel Prize in physics for his work in Machine Learning. Some articles this morning have coined him as the grandfather of AI.   Dr. Hinton is a favourite topic of Canadian IP pundits. By all accounts his AI work at UoT was groundbreaking and, along the way, patents associated with some of it are now owned by Google. It is here that the pundits entered the picture with chatter about the loss of Canadian IP.   I too entered the chatter in 2020, sort of. Okay, it was more like talking to myself. At that time I penned a series of three articles about IP in Canada. The first or these (https://lnkd.in/esE7eKc) considered the loss of technology and IP. I said we need to identify the technology that is being developed and patented and we need to invest.  We need to be on the same playing field as those buying Canadian IP. This is one of my motivations for founding IPmart.   A September 15th Opinion in the Globe & Mail framed the IP discussion in terms of productivity. The authors wrote “… we need to dramatically increase the rate at which we protect and commercialize new ideas and the intellectual property (IP) that often starts in publicly funded research.” Hmmm … that sounds familiar! #technology #patents #CDNtech #IPmart

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🚨 Can AI System Quantify Misinformation in Real-Time? Groundbreaking Research Says Yes! 🚨 📊 Researchers at the University of Waterloo have developed a revolutionary system called U-MAS (UbiLab Misinformation Analysis System) to detect, analyze, and quantify health misinformation on social media as it happens. 🔑 Key features of U-MAS: • 🤖 Uses AI and machine learning to analyze Twitter data • 🧠 Performs topic modeling, sentiment analysis, and misinformation classification • 📈 Provides interactive dashboards with real-time misinformation percentages • ⏳ Enables monitoring of misinformation trends and volumes over time 🧪 The system was tested on fluoride-related misinformation, accurately quantifying the percentage of false information in the dataset. It's now being adapted for vaccine hesitancy and heat illness topics. 💡 U-MAS empowers public health officials and researchers to: • Measure the exact prevalence of misinformation on specific health topics • Identify emerging misinformation trends as a percentage of overall conversation • Develop data-driven, targeted interventions based on quantifiable metrics 🌟 This groundbreaking work puts a number on the spread of health misinformation online, potentially revolutionizing how we combat fake news. Read the full paper here: [Link to paper] #HealthMisinformation #AI #PublicHealth #DataAnalytics​​​​​​​​​​​​​​​​ #HealthMisinformation #AI #PublicHealth #DataAnalytics

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💥 Quantum theorists at UBC Blusson Quantum Matter Institute (Blusson QMI) have proposed a new approach to studying stacking ferroelectricity—spontaneous electric polarization—in layered, two-dimensional lab-grown materials. Ferroelectric materials are unique in their ability to “remember” their new state after the electric field is removed, which makes them useful in applications including solar cell technology and compact memory devices. “We've been learning in recent years that quantum geometry underlies a surprising range of the observable properties of materials,” said Dr. Marcel Franz, deputy scientific director at UBC Blusson QMI and a professor with the Department of Physics & Astronomy. “This work adds an important new entry to the growing list of phenomena that can be elucidated using this fascinating geometric approach.” “The most exciting part of our discovery is that the underlying physics behind stacking ferroelectricity can, in fact, be understood as a geometric property,” said UBC Blusson QMI postdoctoral fellow Dr. Benjamin T. Zhou, lead author of the study published in the journal Physical Review Letters. 👉 Read more: https://lnkd.in/gRSRXf36 #quantum #research #science #innovation #materials #discovery #QuantumBC #QuantumCoast #QuantumCanada

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In my most recent CanInnovate post [1], I interview Lisa Lambert, CEO of Quantum Industry Canada, on the state of quantum technologies in Canada. I have had an eye on this space for a while now, as it is an outlier among deep tech sectors in that Canada is actually leading globally in many respects. My goal in this interview was to understand how this came about, and to understand whether Canada’s path to its leading position in quantum technologies could be replicated in other deep tech sectors. The answer, unsurprisingly, is yes. The interview itself is far too long to attempt to translate into LinkedIn posts (it would take at least 15 posts), so to see Lisa’s full commentary you will have to visit the main article. Many thanks to Lisa for taking the time to give such thoughtful and detailed responses! Instead of the usual full-post summary, here I will draw on Lisa’s responses to attempt an answer to the original question. This is post 1 of 2 toward that goal. Canadian leadership in quantum technologies holds key lessons that generalize to other sectors of deep tech. It represents the combination of four ingredients: a pool of highly trained talent, infrastructure to enable their research, visionary leadership that was willing to make a bet that would not pay off during their tenure, and a catalyst to seed what became a virtuous cycle of innovation. The catalyst was a series of investments made in quantum technologies in the Waterloo region that led to the establishment of the Perimeter Institute. This investment was made decades ago, at a stage when quantum technologies generally were still firmly in the realm of academic research. In the case of quantum technologies, it was the vision of an individual who made a massive philanthropic investment that set Canada on its path to dominance. However, relying on once-in-a-century good will is not a valid strategy. The good news is that there is no obvious reason that the catalyst needs to come from a private individual. Examples abound globally of similar virtuous cycles of innovation catalyzed by public sector investments [2]. The failure of the Canadian public sector to learn this lesson leads to other challenges that were identified in the interview: not only are we the world’s source of intellectual property, but we are the world’s schoolhouse, training and exporting a steady stream of world-class talent. Canada has many deep tech sectors that have three of the four key ingredients: deep talent pools, world-class research infrastructure, and world-leading minds, but without the catalyst, Canada rarely gets past the stage of filing academic IP. If Canada hopes to achieve a similar position of leadership in other sectors, our policy makers will need to step up and provide that catalyst deliberately. Post 2: https://lnkd.in/gWUynQ_T

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I can't agree more. Industry needs to follow through, starting immediately with #PQC aka cryptography hardening to complete the transition before the end of this decade (at the latest). It's time to innovate for real. 👉 DM me to join the industry leader quantum working group in putting together to explore business cases and share lessons learned

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We invite research submissions on Quantum Computing and Reinforcement Learning (QCRL) at IEEE Quantum Week 2024 (Montreal, Sep. 15-20, 2024). https://2024.qcrl.io/ Scope and Topics: Topics relevant to this session include, but are not limited to: - Theoretical studies of quantum reinforcement learning algorithms - Challenges in quantum reinforcement learning in the NISQ era - Quantum reinforcement learning under the influence of quantum device noise QRL in the context of trustworthy ML (e.g., adversarial attacks, federated learning) - Quantum reinforcement learning for scientific discovery, commercial, and industrial applications - Benchmarking QRL algorithms - Reinforcement learning for quantum control, quantum error correction, and quantum error mitigation - Reinforcement learning for quantum architecture search, optimization, and program synthesis - Hybrid RL-QC systems design Important Deadlines: - Jul 10, 2024: Abstract Due Date - Jul 15, 2024: Paper Submission Due Date - Jul 28, 2024: Notification of Paper Acceptance - Aug 5, 2024: Camera-ready Papers Due #quantum #machinelearning #reinforcementlearning

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Check out this great article on the Financial Post about the impressive trajectory of DCS Prof. Sanja Fidler, head of the Nvidia Toronto Research Lab. The feature highlights some of the amazing accomplishments of Prof. Fidler and how she has helped make Nvidia a leader in AI. Read more at https://lnkd.in/gsXB3UgV.

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On October 8, 2024, The Nobel Prize in Physics was awarded to John J. Hopfield from Princeton University and Geoffrey E. Hinton from the University of Toronto for their foundational contributions to machine learning using artificial neural networks. The committee praised their work, stating that "their groundbreaking research has established the basis for today's powerful machine learning systems." When CommonWealth Magazine Group(天下雜誌群)'s reporter I-yun (Elaine) Huang interviewed Geoffrey Hinton seven years ago, he was already celebrated as the "Godfather of #AI" for his pioneering contributions to the field of artificial neural networks. At the time, he was still working for Google Brain. He announced his departure from Google in 2023, citing concerns about the risks of #AI #technology. Reflecting on the 2017 encounter, she recalls: "On an afternoon at Google's Toronto office, Professor Hinton, with his gray hair and plaid shirt, stood throughout the entire interview. The whiteboard in his cramped office was filled with complex formulas that I couldn’t decipher. Back then, he still embraced his lifelong research in AI, unfazed by the potential risks. The world was mesmerized by the deep learning revolution brought about by #AlphaGo, and AI's possibilities continued to inspire him. After the interview, he casually took a bite of the pineapple pastries we had brought from #Taiwan and enthusiastically praised them as if savoring a delightful afternoon tea. Today, however, the humble Hinton is more concerned about the darker side of AI, even expressing regret for his role in its development. He is truly a visionary scientist—a brilliant mind who has shown us both the promise and perils of technology." Read I-yun’s full interview with Geoffrey Hinton. Link in the comments.

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Our paper, "DRAMScope: Uncovering DRAM Microarchitecture and Characteristics by Issuing Memory Commands," was accepted at ISCA 2024! We had an intriguing journey to figure out the sizes of DRAM MATs, common pitfalls regarding address and data mapping in the computer architecture community, coupled-row activation, and RowHammer/RowPress characteristics induced by the 6F^2 DRAM cell structure, to list a few, by issuing ordinary commands to DRAM. We look forward to presenting our paper in Buenos Aires, Argentina. I am really proud of my students and colleagues, without whom I could not imagine to publish this work in a one-and-done manner. Pdf: https://lnkd.in/gnnQS_XA Authors: Hwayong Nam, Seungmin Baek, Minbok Wi, Michael Jaemin Kim, Jaehyun Park, Chihun Song, Nam Sung Kim, and Jung Ho Ahn Abstract: The demand for precise information on DRAM microarchitectures and error characteristics has surged, driven by the need to explore processing in memory, enhance reliability, and mitigate security vulnerability. Nonetheless, DRAM manufacturers have disclosed only a limited amount of information, making it difficult to find specific information on their DRAM microarchitectures. This paper addresses this gap by presenting more rigorous findings on the microarchitectures of commodity DRAM chips and their impacts on the characteristics of activate-induced bitflips (AIBs), such as RowHammer and RowPress. The previous studies have also attempted to understand the DRAM microarchitectures and associated behaviors, but we have found some of their results to be misled by inaccurate address mapping and internal data swizzling or lack of a deeper understanding of the modern DRAM cell structure. For accurate and efficient reverse engineering, we use three tools: AIBs, retention time test, and RowCopy, which can be cross-validated. With these three tools, we first take a macroscopic view of modern DRAM chips to uncover the size, structure, and operation of their subarrays, memory array tiles (MATs), and rows. Then, we analyze AIB characteristics based on the microscopic view of the DRAM microarchitecture, such as 6F^2 cell layout, through which we rectify misunderstandings regarding AIBs and discover a new data pattern that accelerates AIBs. Lastly, based on our findings at both macroscopic and microscopic levels, we identify previously unknown AIB vulnerabilities and propose a simple yet effective protection solution.

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