Geoff Parker

If you are attending ACM SIGMETRICS 2024 this week, don't miss the Sustainable Computing session (aka the "UMass session"), where UMass students will present all three papers in the session! Adam Lechowicz will present "The Online Pause and Resume Problem: Optimal Algorithms and an Application to Carbon-Aware Load Shifting" Read it here: https://lnkd.in/dBQ4C93F Walid Hanafy will present "CarbonScaler: Leveraging Cloud Workload Elasticity for Optimizing Carbon-Efficiency." Read it here: https://lnkd.in/dRzFCNux Adam Lechowicz will also present "Online Conversion with Switching Costs: Robust and Learning-Augmented Algorithms" Read it here: https://lnkd.in/dg3c2p66 Thanks to all co-authors: Noman Bashir David Irwin Adam Wierman Mohammad Hajiesmaili Qianlin Liang #sustainability #cloudcomputing

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Today I present fresh results from two semesters of waitlist control trials at Stevens Institute of Technology's 2nd annual #Teaching and #Learning Symposium. Did #argumentMapping improve individual students' critical thinking and persuasive writing (on average)? Prior research looked merely for between-group differences and didn't control for differences in instructor(s), teaching styles (e.g., active vs. lecture), learning activities (individual vs. group), classroom, day, etc. So I controlled for all that and designed the experiments to be able to test whether each individual's performance improved (on average). I can even test for a dose-response! So far the results are surprising me! They seem to tell a different story than what the prior research reported. Can't wait to get colleagues' input so I can start writing the manuscript — stay tuned for the preprint. #higherEd #EdResearch #Edu #ScienceOfLearning #Logic #Ethics #Visualization #GraphicDesign #Pedagogy #Philosophy #Psychology #Science

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I'm excited to invite you to a special session this Wednesday at 10am PST/1pm EST where we'll explore the transformative journey of digital adaptation in the industrial sector. Vijay Govindarajan (VG) of @The Tuck School of Business at Dartmouth will join Venkat Venkatraman from @Questrom School of Business, Boston University, to unpack insights from their latest book, “Fusion Strategy,” published by @Harvard Business Review. @Chris Tacy, the Chief Strategy Officer at Mach49, will be introducing our talk. In this session, we'll dive into: -The concept of fusion as the future strategy for industrial companies. -The impact of digital disruption on industrial companies in terms of scale, scope, and speed. -The role of real-time data and generative AI in securing a competitive edge. -Strategies for leveraging data network effects to reimagine your company. -Understanding your place within digital ecosystems. Join us to understand how to position your company more competitively with the power of #AI. Secure your spot now: https://bit.ly/3PyyQji

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Very interesting article from Krebs on what appears to be Internet cyber-attacks deployed by Russia against Ukraine and beyond, using multiple Internet providers from different countries, some of them apparently unaware of the abuse. Of interest esp. from the DoS and routing-security aspects.

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We're looking forward to discussing why #Fusionstrategy unlocks value trapped in analog modes of operations that have existed for almost a hundred years. We have seen digital shifts in "information goods" and now know the winners and losers. Incumbents misread the weak signals, and the digital natives stole a march. Will the same trend continue in "industrial sectors?" How could real-time data and AI help those manufacturing physical products across a large swath of the global economy create and deliver more value to their customers? Please join us tomorrow if you have time.

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This week we talk to Justin Reich about artificial intelligence in education. I always really appreciate Justin's perspective -- he started as a history teacher, and while he knows both education and tech through and through, he retains his essentially highly human perspective on new technologies. On the pod, he talks about how Chatgpt is an "arrival" rather than "adoption" technology, why "AI" is sometimes just a label to make things more magical than they are, and how we might constructively engage with these new tools in both schools and society. Check it out: https://lnkd.in/e4vKbGUV

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What sets the fast-movers apart from the rest when new opportunities appear? In their latest article for MIT Sloan Management Review, "Engineer Your Own Luck," Mark Greeven, Howard Yu and Jialu SHAN argue that it's modularity. That is, digital modularity: identifying your core competencies and exposing them to your partners and customers — as in, the Nvidia decision years ago that helped it break way, way out of its original niche position. Read on: https://lnkd.in/eRy-FjzE

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American computer scientist Ray Kurzweil, a prominent figure in artificial intelligence (AI), has long been known for his futuristic predictions. In his bestselling 2005 book, "The Singularity Is Near," Kurzweil forecasted that computers would achieve human-level intelligence by 2029. Fast forward nearly 20 years, at 76 years old, he now introduces a sequel titled "The Singularity Is Nearer," where some of his once deemed "wacky" predictions appear more plausible. Kurzweil, also serving as the principal researcher and AI visionary at Google, recently shared his insights with the Observer, embodying his roles as an author, inventor, and futurist. Read more about Kurzweil's latest perspectives on AI and the future: [Link to the article](https://lnkd.in/dWqhb_P4)

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Are you a scientist or engineer wanting to mobilize your research outside of the laboratory? Discover how the choices you make while conducting lab research can enhance the likelihood of impactful innovation.

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Fascinating research. “For learning to be useful, it has to be remembered,” added Steve Chase, professor of biomedical engineering and the Neuroscience Institute at Carnegie Mellon University and one of the three leads on the project, along with Byron Yu of Carnegie Mellon and Aaron Batista of the University of Pittsburgh. “The process of how you take a learned experience and lay it down in neural activity, so it can be recalled again when you need it, is a fascinating process. Our understanding of it is still in its infancy. The hope is that by looking at how these learned acts are laid down for motor tasks, it will help us know how they’re laid down for other tasks as well. And, ultimately, once we’re able to do all of this, we can try to understand what all the factors that help us remember are, to really track the memory process itself.” https://lnkd.in/gGqdw5-D #learning #memory

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Princeton Engineering is advancing the next generation of wireless technologies by engaging not only with the technology but also with policy — across academia, industry, and government. 

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AI Could Help Overcome the Scarcity Mindset That Has Artificially Constrained HigherEd. Rather than being a function of talent and motivation, access to, and success in, #HigherEd remains highly correlated with nonacademic factors such as race, family income and location. This lack of access to a larger population is often justified through a scarcity mindset based on an argument of (a) limited resources including lack of space at current institutions, (b) lack of suitable locations, resources and modalities of operation for new institutions, (c) insufficient well-qualified faculty and staff, and (d) the consequent inability to provide multiple pathways for learners both into the system and to gaining value through subsequent on-ramps to careers that enable socioeconomic advancement. The scarcity mindset, built on the pervasive belief that resources and opportunities are limited, has been strengthened over the years by higher education’s focus on outdated structures and modalities of interaction and engagement. While this mindset has changed in recent years at institutions such as Arizona State University, Southern New Hampshire University, and Western Governors University, overcoming the challenges perpetuated by a system built on a foundation of exclusivity rather than access, motivation and merit, appears daunting. While advances in AI and other technologies are not the panacea to higher education’s history of exclusion and poor outcomes, they can be a means of changing processes and policies for the better and offer promising mechanisms for dismantling the scarcity mindsets through re-envisioning the existing paradigm, offering the potential of personalized attention and resources to thousands of additional learners, irrespective of location, socioeconomic status, and background, enabling greater levels of learning and career and life success at scale. A recent article in The EvoLLLution: A Modern Campus Illumination describes how AI can help address each of the four scarcity mindsets – #Access, #Location, #Experts & #Pathways. Democratizing access to knowledge and learning is an age-old commitment that higher education has failed to keep. There are now mechanisms that force reflection on, and re-evaluation of, how higher education meets its promise of being the great equalizer and ensuring the activation of talent to opportunity at scale. As AI use continues to evolve, the higher ed community needs to embrace it thoughtfully and responsibly, paving the way for a future where learning is enabled at scale while also being flexible and personalized, breaking the prevalent scarcity mindset and changing it to one of abundance to enable access and opportunity for all. The question is whether we are willing to make that leap. #HigherEd #innovation #Access #AI #Scale #Scarcity #Personalized #Equalizer #Talent #Scarcity #Mindset

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Very good interview of Alex 'Sandy' Pentland who's joining Stanford Institute for Human-Centered Artificial Intelligence (HAI)'s Digital Economy Lab; these 5 arguments especially resonated with me: 1) "We also need to reduce partisan animosity online. Currently, digital media are designed to get us to react quickly, which results in unthinking responses that in turn lead to cascades of behavior where everyone becomes outraged. We need a system that instead encourages people to communicate in ways that support democratic processes rather than tearing them apart. Large-scale experiments find that online discussions are improved when people are encouraged to reflect a little bit on what they are about to say. For example, we see less division and outrage online when we add an extra step that allows time for reflection before replying or forwarding, or add a prompt to consider what a comment will do to your reputation." 2) "we need to draw a line between individual expression and mass expression. For example, consider the case where influencers often have more than a million “friends” on social media. Anyone with that many people following them can make money and build a reputation while saying whatever they want. And I think these overly powerful voices ought to be treated like businesses and not like individuals. They shouldn’t be able to cry “fire” in a crowded theater or tell outright lies. Those are basic standards we demand of other businesses [like] TV news shows or newspapers can’t publish something just to generate outrage. (...) If you’re going to express your ideas to a million people, then you’re a business and you ought to be regulated like a business." 3) "In some cases, fixing the problem will require changing often subtle little things down in the guts of the internet. As an example, if someone is producing 50,000 tweets a day, that’s a bot, not a human. That’s an obvious case, but there are other things we can do to find bots more efficiently, determine when foreign nations are interfering in elections, and better deal with ransomware and cyberattacks. The problems we have now evolved because the architecture of the internet was never completed. And now maybe the time has finally come to finish the job." 4) "it’s not artificial general intelligence, or AGI, that worries me. It’s that AI is becoming pervasive in so many parts of our lives, including our medical system, our transportation system, and our schooling system. It’s going to be everywhere, just like the previous waves of AI were. And we need to make sure that it’s prosocial." 5) "AI has always been and continues to be a way of finding and using patterns in data. So, if you want to control AI, you have to control the data it feeds on by demanding privacy rights and ownership rights over data. Without that, AI will just run amok. Data are like the food for AI, and if you want to control AI, you have to control the data."

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Wow, I've not encounter others with so much similar thinking to us. We do have a different conclusion, however. They note that spatial AI will enable generality, but data scarcity is a bottleneck. We ask the question "is the data being collected today the right kind?" LLMs operate on text input to ouput text; the data modality doesn't change. Robot AI needs to understand and operate on dynamics and motion, but when the inputs are intermittent snapshots and LiDAR scans, too much detail is lost to actually understand what's going on. It's like a human doing anything under a flashing strobe light: they'd mess up a lot! It's pretty obvious that robots will need to see like humans to be as capable as humans (and to be clear, video is very much not like how humans see). So yes, there is a data scarcity problem in that the correct data is not being captured with current systems. Our approach builds on exciting new hardware to let robots fully understand and predict motion, so that in the end *significantly* less data is actually needed to learn and generalize.

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Offering a new course this summer in Optimization Models and Algorithms with Bulent Soykan at School of Modeling, Simulation, & Training

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The AI-Powered Future of Regulation: A Collaborative Vision for Innovation The regulatory landscape of tomorrow promises a radical departure from today's often cumbersome and reactive model. AI is poised to revolutionize how we design, implement, and enforce regulations, ushering in unprecedented collaboration, efficiency, and public benefit. Imagine a world where regulators and industry work hand-in-hand, empowered by AI-driven tools that foster transparent communication and shared understanding. This collaborative approach, fueled by data-driven insights and predictive modelling, could enable the development of effective regulations that also allow the industry ample time to adjust. AI-powered compliance platforms could become indispensable business partners, providing real-time alerts, guidance, and streamlined processes that transform compliance from a burden into a strategic advantage. Regulatory sandboxes could evolve into dynamic innovation hubs where regulators and businesses collaborate to test emerging technologies within a controlled environment, ensuring public safety while fostering innovation. The path to this AI-powered future requires a concerted effort from all stakeholders. Governments must invest in AI infrastructure and talent, while businesses must embrace AI as a strategic tool for compliance and innovation. Collaboration between the public and private sectors will ensure that AI is deployed ethically and responsibly, focusing on transparency, accountability, and fairness. The promise of AI in regulation is immense, but much work remains to be done. By fostering collaboration, empowering data-driven decision-making, and promoting efficiency and predictability, AI could help us build a regulatory landscape that is truly fit for the 21st century. Let's embrace this opportunity to transform regulation from a constraint into a catalyst for innovation and progress. Our country needs it! Previous efforts at regulatory reform leave us wanting. #AI #ArtificialIntelligence #Regulation #Compliance #Innovation #DataDriven #Transparency #Collaboration #EthicalAI #FutureOfWork #PublicPrivatePartnerships #TechInnovation #AIRegulation #Efficiency #Accountability #PredictiveModeling #AlgonquinCollege #ThomasConway

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Adapting our research and regulatory processes to keep pace with GenAI technologies is crucial. Our participation in the Federation of American Scientists policy sprint is an attempt to provide a framework for legislators to use to expedite high quality research for instructional programs using GenAI. Failure to do so exposes students to ineffective or harmful educational tools, exacerbates inequities, and hinders our ability to prepare students for success. The rapid advancement of GenAI offers unprecedented opportunities for personalized learning and support, but the slow pace of traditional research and evaluation processes poses significant risks. To address this, we propose three key actions: 1. Establish the GenAI in Education Research Accelerator Program (GenAiRA) to expedite efficacy research on GenAI-powered tools. 2. Adapt IES research processes to allow for rapid assessment of GenAI technologies. 3. Create a GenAI Education Research and Innovation Consortium to foster collaboration among schools, researchers, and EdTech developers. Implementing these recommendations will ensure GenAI tools are safe, effective, and equitable, helping to close learning gaps and improve outcomes for all students. Cc: coauthors: Anastasia Betts, Ph.D. Diana Hughes, MFA Erin Lenihan, M.Ed. Age of Learning, EDSAFE AI Alliance #policy #innovation #education #evidence Policy paper in comments.

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This conversation with Prof. John L Hennessey, co-inventor of RISC and a pioneering technologist in computer architecture, is filled with wisdom for entrepreneurs, and leaders large. In this conversation, he discusses in the context of his book "Leading Matters." He speaks about his setbacks, lessons learned, entrepreneurship, leadership, etc. This conversation happened several years ago. https://lnkd.in/ea2bJXQr #innovationscaleupadvisors #entrepreneurialleadership

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