https://pharma.intelligence-synthesis.com/en/ai-reports/From AI companies, universities, research institutes and consulting firmsenhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/145e91d47a/ir-145e91d47aSat, 17 Oct 2026 00:00:00 +0900labNVIDIA has launched RTX Spark laptops, with retail launch events held around the world, including one in Berlin where CEO Jensen Huang made an appearance. The chip combines a Blackwell RTX GPU and a Grace CPU in one superchip, offering up to 1 petaflop of AI compute and up to 128GB of unified memory. Laptops from ASUS, Dell, HP, Lenovo, Microsoft and MSI start at $2,399, with more systems on the way. https://blogs.nvidia.com/blog/local-ai-rtx-spark-windows-laptops-celebration/https://pharma.intelligence-synthesis.com/en/ai-reports/s/fc6ef85e79/ir-fc6ef85e79Sat, 17 Oct 2026 00:00:00 +0900academiaThis paper proposes a safety case template for offensive cyber capabilities. It breaks the main claim into progressively specific sub-claims, each supported by evidence, and links risk models, proxy tasks, and evaluation results using the Claims Arguments Evidence framework. The authors present it as a proof of concept to encourage discussion on AI safety cases. https://www.governance.ai/research-paper/safety-case-template-for-frontier-ai-a-cyber-inability-argumenthttps://pharma.intelligence-synthesis.com/en/ai-reports/s/fb171eb97f/ir-fb171eb97fSat, 17 Oct 2026 00:00:00 +0900academiaThis article gives an overview of how progress in hardware, specifically compute, underpins further improvements in AI systems. It explains that AI progress rests on compute, data, and algorithms, and describes common compute metrics such as FLOPS, MIPS, and IOPS. It is the third in a series on AI trends. https://futuretech.mit.edu/news/what-drives-progress-in-ai-trends-in-computehttps://pharma.intelligence-synthesis.com/en/ai-reports/s/fabc33faa3/ir-fabc33faa3Sat, 17 Oct 2026 00:00:00 +0900academiaNew research finds that machine learning frameworks can lose more than 40% of their key functions when ported to other hardware. Even where functions remain portable, performance can slow so much that it becomes untenable. The authors suggest that hardware specialization may impede innovation in machine learning research. https://futuretech.mit.edu/news/the-grand-illusion-the-myth-of-software-portability-and-implications-for-ml-progresshttps://pharma.intelligence-synthesis.com/en/ai-reports/s/f4f0a1b4e7/ir-f4f0a1b4e7Sat, 17 Oct 2026 00:00:00 +0900academiaThe US and EU use training compute thresholds, the number of computational operations used in training, to identify general-purpose AI models that may pose risks of large-scale societal harm. The authors argue that training compute is currently the most suitable metric for this initial filter, since it correlates with capabilities and risks, is quantifiable, and can be verified externally. They caution that it is an imperfect proxy for risk and should not be used alone to determine mitigation measures. https://www.governance.ai/research-paper/training-compute-thresholds-features-and-functions-in-ai-regulationhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/f2e2436481/ir-f2e2436481Sat, 17 Oct 2026 00:00:00 +0900academiaDrawing on academic studies and public polling, this report synthesizes public attitudes toward AI, focusing on the United Kingdom and United States. It covers views on issues such as concern about job loss, along with emerging trends, challenges, and opportunities. It also introduces the AI SHARE database, which aggregates survey data from over 200 studies conducted between 2014 and 2023. https://www.governance.ai/research-paper/what-does-the-public-think-about-aihttps://pharma.intelligence-synthesis.com/en/ai-reports/s/f14403359b/ir-f14403359bSat, 17 Oct 2026 00:00:00 +0900academiaThe paper argues that flaw-reporting infrastructure, practices, and norms for general-purpose AI (GPAI) systems are seriously underdeveloped compared with software security. It proposes standardized AI flaw reports and rules of engagement, broadly scoped disclosure programs modeled on bug bounties with legal safe harbors, and better infrastructure to coordinate flaw reports across stakeholders. https://www.governance.ai/research-paper/in-house-evaluation-is-not-enough-towards-robust-third-party-flaw-disclosure-for-general-purpose-aihttps://pharma.intelligence-synthesis.com/en/ai-reports/s/f130afe88a/ir-f130afe88aSat, 17 Oct 2026 00:00:00 +0900academiaAs AI agents increasingly plan and carry out tasks in open-ended environments, the authors argue that existing tools are insufficient to manage their risks. They propose 'agent infrastructure,' meaning technical systems and shared protocols external to agents that mediate their interactions and impacts. The authors identify three functions: attributing actions to specific agents or users, shaping agents' interactions, and detecting and remedying harmful actions. https://www.governance.ai/research-paper/infrastructure-for-ai-agentshttps://pharma.intelligence-synthesis.com/en/ai-reports/s/effaa42816/ir-effaa42816Sat, 17 Oct 2026 00:00:00 +0900academiaAI systems could cause immense harm but also greatly improve human welfare, so the regulatory challenge is to enable innovation while avoiding risks. The paper argues that regulatory supervision, where officials have information-gathering powers and significant discretion, should be used only where no other approach can achieve the regulatory objective. It concludes that supervision is warranted for frontier AI developers such as OpenAI, Anthropic, Google DeepMind and Meta, because no other form of regulation can achieve good AI policy. https://www.governance.ai/research-paper/regulatory-supervision-of-frontier-ai-developershttps://pharma.intelligence-synthesis.com/en/ai-reports/s/ed85089ac3/ir-ed85089ac3Sat, 17 Oct 2026 00:00:00 +0900academiaThis interactive web app explores the dynamics of risky AI competition through the safety-performance tradeoff (SPT) model. It asks whether AI safety breakthroughs will always lead to safer systems, even when everyone knows how to make their systems safer. The tool lets users examine why deployed AI systems may remain as risky as they were before a breakthrough. https://www.governance.ai/research-paper/safety-performance-tradeoff-model-web-aphttps://pharma.intelligence-synthesis.com/en/ai-reports/s/ed8394bd48/ir-ed8394bd48Sat, 17 Oct 2026 00:00:00 +0900academiaAs AI systems grow more capable, they will increasingly be used to cause harm, such as automating fraud or creating harmful fake images. The paper argues that restrictions on capabilities are warranted when other interventions are insufficient, potential harm is high, and targeted intervention is possible. It offers a taxonomy and framework centered on the steps needed for misuse to cause harm, and applies it to predicting novel toxins, creating harmful images, and automating spear phishing. https://www.governance.ai/research-paper/protecting-society-from-ai-misuse-when-are-restrictions-on-capabilities-warrantedhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/ed4b9a2808/ir-ed4b9a2808Sat, 17 Oct 2026 00:00:00 +0900academiaThe paper proposes a framework for assessing how LLMs and related technologies may affect work, based on their relevance to the tasks workers perform. Applying it with both humans and an LLM, the authors estimate that about 1.8% of jobs could have over half their tasks affected by LLMs with simple interfaces and general training. Accounting for complementary software developments, that share rises to just over 46%. https://www.governance.ai/research-paper/gpts-are-gpts-labor-market-impact-potential-of-llmshttps://pharma.intelligence-synthesis.com/en/ai-reports/s/ea2245c67e/ir-ea2245c67eSat, 17 Oct 2026 00:00:00 +0900academiaThis FutureTech post summarizes some key insights from the 2025 conference, 'How Fast Will AI Automation Happen?', held in October. Presenters included leading researchers on AI development, the economics of AI, and AI applications. The post highlights selected ideas rather than offering a full summary of each talk. https://futuretech.mit.edu/news/how-fast-will-ai-automation-happen-reflections-on-the-futuretech-conferencehttps://pharma.intelligence-synthesis.com/en/ai-reports/s/e3a14b19e4/ir-e3a14b19e4Sat, 17 Oct 2026 00:00:00 +0900academiaThis submission responds to a US request for information on NIST's tasks under the AI executive order, focusing on "dual-use foundation models." It recommends that developers be encouraged to adopt practices such as publishing safety policies, conducting red-teaming, producing risk estimates, and monitoring models after deployment. It also argues that risk management burdens should be proportionate to a system's impact. https://www.governance.ai/research-paper/response-to-the-rfi-related-to-nists-assignments-under-the-executive-order-concerning-aihttps://pharma.intelligence-synthesis.com/en/ai-reports/s/e36a0f3452/ir-e36a0f3452Sat, 17 Oct 2026 00:00:00 +0900academiaThe online activities of AI agents could distort human beliefs, for example by making synthetic likes and shares look like genuine opinion. The author argues that Article 50 of the EU AI Act, expected to take effect on 2 August 2026, likely requires labeling of AI agents' web requests and browser actions, and that labels should be verifiable in terms of creator and tampering. The brief proposes potential text for the upcoming Code of Practice in an appendix. https://www.governance.ai/research-paper/labeling-of-ai-agent-activity-in-article-50-of-the-eu-ai-acthttps://pharma.intelligence-synthesis.com/en/ai-reports/s/e086420a53/ir-e086420a53Sat, 17 Oct 2026 00:00:00 +0900academiaThe paper focuses on 'frontier AI' models: highly capable foundation models that could possess dangerous capabilities sufficient to pose severe risks to public safety. It argues that regulating them requires three building blocks: standard-setting, registration and reporting requirements, and mechanisms to ensure compliance. It also proposes an initial set of safety standards, including pre-deployment risk assessments and monitoring and responding to new information after deployment. https://www.governance.ai/research-paper/frontier-ai-regulation-managing-emerging-risks-to-public-safetyhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/dd9a29f1e1/ir-dd9a29f1e1Sat, 17 Oct 2026 00:00:00 +0900consultinghttps://www.deloitte.com/global/en/services/consulting-risk/perspectives/the-ciso-guide-to-generative-ai-opportunities-outcomes-and-the-urgency-of-now.htmlhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/dc607dd2d3/ir-dc607dd2d3Sat, 17 Oct 2026 00:00:00 +0900academiaThe report analyzes how generative AI, emerging AI agents and, more speculatively, artificial general intelligence will affect finance. It examines four functions: financial intermediation, insurance, asset management, and payments, along with implications for financial stability and prudential policy. It also considers spillover effects on the real economy under optimistic and disruptive scenarios, and proposes a framework for upgrading financial regulation based on general AI governance principles. https://www.governance.ai/research-paper/intelligent-financial-system-how-ai-is-transforming-financehttps://pharma.intelligence-synthesis.com/en/ai-reports/s/db7d10cae9/ir-db7d10cae9Sat, 17 Oct 2026 00:00:00 +0900academiaA pre-registered randomized controlled trial (June to August 2025, n = 153) found no significant difference in workflow completion for novices using LLM assistance versus internet access on a task modeling a viral reverse genetics workflow. The LLM arm had numerically higher success rates in four of five tasks, which the authors associate with a modest performance benefit. The study points to a gap between benchmark results and real-world utility and calls for physical-world validation of AI biosecurity assessments. https://www.governance.ai/research-paper/measuring-mid-2025-llm-assistance-on-novice-performance-in-biologyhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/d8e7de3025/ir-d8e7de3025Sat, 17 Oct 2026 00:00:00 +0900academiaThe paper argues that compute providers should have legal obligations and ethical responsibilities in AI regulation, acting as securers, record keepers, verifiers of customer activity and enforcers. It examines how these functions can be performed in a targeted, privacy-conscious way, using non-confidential data to infer workload type and compute consumed. Using US Executive Order 14110 as a case study, it outlines record-keeping requirements and explores how verification and enforcement could form a broader oversight scheme. https://www.governance.ai/research-paper/governing-through-the-cloudhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/d6e43c0d75/ir-d6e43c0d75Sat, 17 Oct 2026 00:00:00 +0900academiaOne survey finds that about half of Americans think increased AI use will lead to greater income inequality and a more polarized society. Economists are generally less worried than the public about drastic near-term job loss, but often share concerns about inequality. Several studies find that within occupations such as law and software engineering, the least skilled or least experienced workers gain the most productivity from AI, a result some economists see as a possible route to reducing inequality. https://www.governance.ai/research-paper/ais-impact-on-income-inequality-in-the-ushttps://pharma.intelligence-synthesis.com/en/ai-reports/s/d6d581ae13/ir-d6d581ae13Sat, 17 Oct 2026 00:00:00 +0900academiaAI progress is creating a growing range of risks and opportunities, and the barriers to navigating them are often at least partly technical. The paper explains technical AI governance, which uses technical analysis and tools to support effective AI governance, and presents a taxonomy and an incomplete catalog of its open problems. It is intended as a resource for technical researchers and research funders. https://www.governance.ai/research-paper/open-problems-in-technical-ai-governancehttps://pharma.intelligence-synthesis.com/en/ai-reports/s/d41fec63e3/ir-d41fec63e3Sat, 17 Oct 2026 00:00:00 +0900academiaThe paper outlines four distinct meanings of “AI democratization.” Three of them are used almost interchangeably with “increasing accessibility,” while the governance meaning balances accessibility against other societal needs and values. The authors warn against using the term loosely as a stand-in for “all things good,” since its value depends on alignment with those affected. https://www.governance.ai/research-paper/democratising-ai-multiple-meanings-goals-and-methodshttps://pharma.intelligence-synthesis.com/en/ai-reports/s/cc0371f85c/ir-cc0371f85cSat, 17 Oct 2026 00:00:00 +0900academiaThis white paper examines practical ways to increase the voice and access of the Global AI Majority in AI governance and capabilities, while addressing the security and commercial concerns of frontier AI states. It identifies barriers such as limited digital and compute infrastructure, concentrated AI development, Anglocentric data, and uneven talent distribution. It proposes interest alignment, participatory architecture, and safety assurance as three approaches. https://www.governance.ai/research-paper/voice-and-access-in-ai-global-ai-majority-participation-in-artificial-intelligence-development-and-governancehttps://pharma.intelligence-synthesis.com/en/ai-reports/s/cb9d9704e5/ir-cb9d9704e5Sat, 17 Oct 2026 00:00:00 +0900academiaThis white paper proposes a framework for identifying which AI governance issues should be internationalised, analysing nine policy areas across data, compute, and model governance. It assesses four factors: cross-border externalities, regulatory arbitrage, uneven governance capacity, and interoperability. The benefits of internationalisation are strongest for compute-provider oversight, content provenance, model evaluations, incident monitoring, and risk management protocols, and lower or mixed for data privacy, data provenance, chip distribution, and bias mitigation. https://www.governance.ai/research-paper/what-should-be-internationalised-in-ai-governancehttps://pharma.intelligence-synthesis.com/en/ai-reports/s/ca939387c9/ir-ca939387c9Sat, 17 Oct 2026 00:00:00 +0900consultingDeloitte Consulting LLP announced AI Advantage for CFOs, an integrated AI-powered analytics and insights platform built with Amazon Bedrock and Anthropic's large language models. It includes Finance Automation Agents for automating key finance processes and generating insights from structured, unstructured and multimodal content. Volkswagen Group Argentina is among the first clients to use it. https://www.deloitte.com/global/en/about/press-room/deloitte-launches-ai-advantage-for-cfos.htmlhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/ca2e08e189/ir-ca2e08e189Sat, 17 Oct 2026 00:00:00 +0900academiaA Forbes article explores the convergence of AI and quantum computing and features MIT FutureTech's Quantum Economic Advantage Calculator, presented at the Business of Quantum Summit. It also points to growing quantum investment and to European startups such as Multiverse Computing, which has released compressed AI models. https://futuretech.mit.edu/news/forbes-covers-mit-futuretech-quantum-advantage-calculatorhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/c966d1094b/ir-c966d1094bSat, 17 Oct 2026 00:00:00 +0900academiaRobert Trager discusses Stuart Russell's writings on autonomous weapons and suggests nonproliferation as an alternative to an outright ban. He argues that major powers are unlikely to give up militarily important technologies, so preventing the spread of advanced versions could be a workable approach. He acknowledges that it is difficult and uncertain, requiring major-power focus and security guarantees, but argues it could be worth trying. https://www.governance.ai/research-paper/deliberating-autonomous-weaponshttps://pharma.intelligence-synthesis.com/en/ai-reports/s/c94afb835b/ir-c94afb835bSat, 17 Oct 2026 00:00:00 +0900academiaSome AI companies include provisions in their safety frameworks that let them lower their mitigations if a competitor releases a model with similar capabilities but weaker mitigations. The authors argue this approach could increase total risk, since competitors' capabilities and mitigations are hard to evaluate and accident risks scale with user numbers. They also warn that safety standards could erode suddenly, if one defector triggers others, or gradually through a 'boiling frog' effect. https://www.governance.ai/research-paper/assessing-risk-relative-to-competitors-an-analysis-of-current-ai-company-policieshttps://pharma.intelligence-synthesis.com/en/ai-reports/s/c771955ce6/ir-c771955ce6Sat, 17 Oct 2026 00:00:00 +0900academiaMIT FutureTech's research and operations were featured at the Nvidia GTC conference. Tess Fagan, Head of Operations at MIT, is hosting an AMA session at GTC 2025 on Wednesday, March 19 at 9 a.m. https://futuretech.mit.edu/news/futuretech-at-nvidia-gtchttps://pharma.intelligence-synthesis.com/en/ai-reports/s/c75bf23ceb/ir-c75bf23cebSat, 17 Oct 2026 00:00:00 +0900academiaThis submission responds to the NTIA's AI Accountability Policy Request for Comment and focuses on audits and assessments of foundation models. It argues that foundation models should at least be evaluated for dangerous capabilities, alignment, and truthfulness. It also calls for an ecosystem of independent expert auditors with access to the models and strong incentives to find flaws rather than tick boxes. https://www.governance.ai/research-paper/response-to-the-ntia-ai-accountability-policyhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/c31be07155/ir-c31be07155Sat, 17 Oct 2026 00:00:00 +0900academiaAs frontier large language models become more deeply integrated into society and the economy, the authors argue that decisions about their training, deployment, and use should not rest solely with developers. They propose external scrutiny through methods such as red-teaming, auditing, and external researcher access. The paper organizes six requirements for effective external scrutiny under the ASPIRE framework and offers recommendations to policymakers. https://www.governance.ai/research-paper/towards-publicly-accountable-frontier-llmshttps://pharma.intelligence-synthesis.com/en/ai-reports/s/bd9b8129ac/ir-bd9b8129acSat, 17 Oct 2026 00:00:00 +0900academiaMIT IDE researchers review evidence on AI at work, including where companies go wrong. They find that AI does not automatically replace workers and often creates new coordination and oversight demands. Gains can be real when organizations rethink workflows and invest in human capability alongside AI. https://futuretech.mit.edu/news/effective-ai-in-the-workplace-what-the-research-showshttps://pharma.intelligence-synthesis.com/en/ai-reports/s/bd5ba51c40/ir-bd5ba51c40Sat, 17 Oct 2026 00:00:00 +0900academiaNeil Thompson and colleagues from MIT FutureTech, The Productivity Institute, and IBM's Institute for Business Value have published a new article introducing an AI task automation model. It offers an end-to-end framework that determines the technical performance tasks require, defines the characteristics of AI systems capable of that performance, and guides economic decisions about their development and deployment. https://futuretech.mit.edu/news/beyond-ai-exposure-which-tasks-are-cost-effective-to-automate-with-computer-visionhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/ba5251860d/ir-ba5251860dSat, 17 Oct 2026 00:00:00 +0900academiaThe DRUID conference in Nice, France, from June 13 to 15 this summer will host a debate on how AI development affects knowledge-intensive industries, focusing on the potential for significant deskilling. Maria Savona (University of Sussex) and Neil Thompson (MIT) will argue for the motion, while Hyunjin Kim (INSEAD) and Abhishek Nagaraj (UC Berkeley) will present opposing views. https://futuretech.mit.edu/news/druid-conference-debating-ais-impact-on-knowledge-intensive-industrieshttps://pharma.intelligence-synthesis.com/en/ai-reports/s/b91bd8e1c3/ir-b91bd8e1c3Sat, 17 Oct 2026 00:00:00 +0900academiaMIT FutureTech is holding a workshop on the role of AI in science. It brings together scientists from different fields to discuss the topic. The workshop is invite-only. https://futuretech.mit.edu/news/futuretech-announces-workshop-on-the-role-of-ai-in-sciencehttps://pharma.intelligence-synthesis.com/en/ai-reports/s/b427bcd51c/ir-b427bcd51cSat, 17 Oct 2026 00:00:00 +0900academiaThe article asks what role tort law can play in ensuring responsible frontier AI development, both before and after regulatory regimes are established. It notes that such systems may bring large benefits but also serious risks to public welfare, individual rights and national security. It argues that relying entirely on industry self-regulation is unwise, so the legal system has an important role in ensuring frontier AI companies take reasonable care. https://www.governance.ai/research-paper/tort-law-and-frontier-ai-governancehttps://pharma.intelligence-synthesis.com/en/ai-reports/s/b38e6cebfe/ir-b38e6cebfeSat, 17 Oct 2026 00:00:00 +0900academiaFrontier AI systems could pose growing risks to public safety and security, which raises the question of how much risk is acceptable. The authors recommend that companies first define risk thresholds, use them to set capability thresholds, and then mainly rely on capability thresholds for decisions, noting that risk thresholds are harder to evaluate reliably. They also argue that regulators should explore this area because they are the most legitimate actors to define risk thresholds. https://www.governance.ai/research-paper/risk-thresholds-for-frontier-aihttps://pharma.intelligence-synthesis.com/en/ai-reports/s/b326f406b7/ir-b326f406b7Sat, 17 Oct 2026 00:00:00 +0900academiaBenjamin Manning explained at a recent lab meeting how large language models (LLMs) could revolutionize social science research. Economics often models people as idealized rational agents ('homo economicus'), whereas LLMs enable computational models of humans ('homo silicus'). Early evidence suggests these models can qualitatively replicate human experiments, allow cheaper and faster experimentation, and avoid some ethical barriers. https://futuretech.mit.edu/news/presentation-what-can-we-learn-from-homo-silicus-how-large-language-models-llms-may-revolutionize-social-science-researchhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/b213578d18/ir-b213578d18Sat, 17 Oct 2026 00:00:00 +0900academiaMIT FutureTech Director Neil Thompson presented at the 4th Annual AI in Action Conference at the World Bank in Washington, D.C. The conference was a cross-sector dialogue on how AI is reshaping firms, labor markets, skills, and organizational strategy. His talk was titled 'Meek Models Shall Inherit the Earth.' https://futuretech.mit.edu/news/making-ai-work-what-firms-and-workers-needhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/b1f54a2f21/ir-b1f54a2f21Sat, 17 Oct 2026 00:00:00 +0900academiaThis paper reports an expert survey (N = 166) and a public consultation on thresholds for advanced AI systems, conducted between August and October 2024. Participants generally agreed that thresholds should be set by multiple stakeholders and that different types of threshold should serve specific purposes. They were divided on the role of training compute thresholds and on how many thresholds there should be. https://www.governance.ai/research-paper/survey-on-thresholds-for-advanced-ai-systemshttps://pharma.intelligence-synthesis.com/en/ai-reports/s/b07d86e79e/ir-b07d86e79eSat, 17 Oct 2026 00:00:00 +0900academiaIn a live-recorded CSAIL Alliances Podcast at the MIT Museum, host Kara Miller spoke with David Autor and Neil Thompson about AI and the future of work. The discussion covered how AI reshapes tasks rather than just jobs, why productivity gains have been uneven, and the risks of over-reliance on AI. https://futuretech.mit.edu/news/ai-and-our-time-at-work---mit-csail-podcasthttps://pharma.intelligence-synthesis.com/en/ai-reports/s/b02aad46c9/ir-b02aad46c9Sat, 17 Oct 2026 00:00:00 +0900academiaThis article compares projections of Generative AI's economic impact with those of other technologies, both modern and historical. It considers the impact along two measures, GDP and productivity. Expert claims about Generative AI's effects range from a significant boost to developed-economy GDP to a complete restructuring of the global labor market. https://futuretech.mit.edu/news/putting-the-economic-impact-of-genai-into-scalehttps://pharma.intelligence-synthesis.com/en/ai-reports/s/af81602ec2/ir-af81602ec2Sat, 17 Oct 2026 00:00:00 +0900academiaGreat powers are entering an era of intense competition to master security-relevant technologies such as AI, which can create shared risks like inadvertent crisis escalation and uncontrolled proliferation. Using a strategic model, the authors find that whether a laggard deploys risky technology depends on how adversarial competitors are and how close the laggard is to the leader's capability. They also find that when rivals are not deploying the riskiest technologies, safety measures can be weakened or reversed by risk compensation. https://www.governance.ai/research-paper/safety-not-guaranteed-international-strategic-dynamics-of-risky-technology-raceshttps://pharma.intelligence-synthesis.com/en/ai-reports/s/acbd6f9290/ir-acbd6f9290Sat, 17 Oct 2026 00:00:00 +0900academiaNew research suggests AI systems built or run with limited resources could soon match leading larger models at much lower cost, which could broaden access. MIT FutureTech researchers argue, based on neural scaling laws, that the 'bigger is better' approach may be reaching diminishing returns. They find the drop in gains may eventually leave companies with little advantage from scaling faster than others. https://futuretech.mit.edu/news/the-rise-of-smaller-meek-models-could-democratize-ai-systemshttps://pharma.intelligence-synthesis.com/en/ai-reports/s/ac591734a4/ir-ac591734a4Sat, 17 Oct 2026 00:00:00 +0900academiaThe subtitle of a Verge article says Trump's Tech Corps initiative is turning unpaid workers into Silicon Valley salespeople. Meicen Sun says the recruits will promote U.S. tech in emerging markets, where China already leads in marketing and promotion. https://futuretech.mit.edu/news/the-peace-corps-is-recruiting-volunteers-to-sell-ai-to-developing-nationshttps://pharma.intelligence-synthesis.com/en/ai-reports/s/abba097d09/ir-abba097d09Sat, 17 Oct 2026 00:00:00 +0900academiaThis article outlines how AI models' data requirements may be growing faster than the supply of suitable data. Annual new data creation grew 32-fold from 2010 to 2020, but this still fails to keep up with demand. Analysis by Epoch suggests several data sources, such as high-quality language data, will be exhausted within the next few years. https://futuretech.mit.edu/news/what-drives-progress-in-ai-trends-in-datahttps://pharma.intelligence-synthesis.com/en/ai-reports/s/a9cbccf665/ir-a9cbccf665Sat, 17 Oct 2026 00:00:00 +0900academiaThe MIT AI Risk Repository, a FutureTech initiative, released comprehensive findings mapping the AI governance landscape. The findings show how AI risks are being addressed across different sectors and jurisdictions, and the repository is intended as a tool for researchers, policymakers, and practitioners. https://futuretech.mit.edu/news/mit-ai-risk-repository-releases-impactful-findingshttps://pharma.intelligence-synthesis.com/en/ai-reports/s/a67f1ccbb8/ir-a67f1ccbb8Sat, 17 Oct 2026 00:00:00 +0900academiaThe article analyzes Article 9 of the proposed EU AI Act, its key risk management provision, which is described as the first comprehensive attempt to regulate AI in a major jurisdiction. It explains the regulatory concept and purpose of Article 9, its scope, how its requirements should be interpreted, and how they could be enforced. The article aims to help providers of high-risk systems comply and to inform revisions to the draft and the development of harmonized AI risk management standards. https://www.governance.ai/research-paper/risk-management-in-the-artificial-intelligence-acthttps://pharma.intelligence-synthesis.com/en/ai-reports/s/a5c2450a2a/ir-a5c2450a2aSat, 17 Oct 2026 00:00:00 +0900academiaFutureTech has launched a Substack publication to share research insights and analysis on AI and computing innovation. The aim is to explain complex research in accessible terms for a broader audience. https://futuretech.mit.edu/news/futuretech-launches-substackhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/a4edaf1a65/ir-a4edaf1a65Sat, 17 Oct 2026 00:00:00 +0900academiaThe paper argues that computing power is an effective point of intervention for governing AI, because it is detectable, excludable, quantifiable, and produced through a concentrated supply chain. It notes that governments and companies have started to use compute in AI policy, though the readiness of different compute-based policies varies. It warns that poorly scoped approaches could create risks for privacy, economic impacts, and centralization of power, and suggests guardrails to minimize them. https://www.governance.ai/research-paper/computing-power-and-the-governance-of-artificial-intelligencehttps://pharma.intelligence-synthesis.com/en/ai-reports/s/a4ca602958/ir-a4ca602958Sat, 17 Oct 2026 00:00:00 +0900consultingDeloitte notes that AI and generative AI create new business opportunities but also bring cybersecurity risks during development, deployment and use. The growing attack surface and attackers' use of AI call for a holistic defense covering applications, data, infrastructure and models. The excerpt is cut off, so this summary covers only its opening sections. https://www.deloitte.com/global/en/services/consulting-risk/perspectives/cybersecurity-meets-ai-genai.htmlhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/a283897738/ir-a283897738Sat, 17 Oct 2026 00:00:00 +0900academiaThe authors analyzed every move in 69,974 professional Go games from 2003 to 2021 to study how human players and AI interact to create new knowledge. After AI-powered Go programs surpassed the best human player in 2017, professionals changed their first moves and first invasion moves and adopted different standard opening patterns. However, this AI-driven knowledge came with more concentrated and less diverse moves, and the effect was greater for highly skilled players. https://futuretech.mit.edu/news/standing-on-the-shoulders-of-ai-pushing-the-knowledge-frontier-by-learning-from-aihttps://pharma.intelligence-synthesis.com/en/ai-reports/s/a1d967123b/ir-a1d967123bSat, 17 Oct 2026 00:00:00 +0900academiaThis case study follows Modulate, a company co-founded in 2017 by two MIT alumni to commercialize real-time synthetic voice technology built on GANs. The founders wanted to prevent misuse of a technology that can match the timbre of almost anyone, while staying competitive and keeping investors satisfied. The toolkit, from Harvard Law School Library and the Berkman Klein Center, is meant to spark discussion of the conflicts they faced. https://cyber.harvard.edu/publication/2020/modulate-case-studyhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/a0c10fc630/ir-a0c10fc630Sat, 17 Oct 2026 00:00:00 +0900academiaMIT's new interactive AI Risk Navigator connects to the AI Risk Repository, a living database of over 1,700 AI risks categorized by cause and risk domain, through a shared taxonomy. It lets users move between the datasets and surface the patterns that matter. https://futuretech.mit.edu/news/mit-ai-risk-navigatorhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/9cd12c3c78/ir-9cd12c3c78Sat, 17 Oct 2026 00:00:00 +0900academiaThe paper analyzes how output and wages evolve under different scenarios of technological progress toward Artificial General Intelligence, defined as AI able to perform all tasks humans can. It models human work as tasks of varying complexity, with wages determined by a race between automation and capital accumulation. Depending on the distribution of task complexity, wages may rise indefinitely or collapse once full automation is reached. https://www.governance.ai/research-paper/scenarios-for-the-transition-to-agihttps://pharma.intelligence-synthesis.com/en/ai-reports/s/9cc2159532/ir-9cc2159532Sat, 17 Oct 2026 00:00:00 +0900consultingAccording to a Fortune/Deloitte survey, 79% of CEOs say accelerating innovation is a top use case for generative AI. Deloitte finds that digital transformations are more successful when CEOs take a leadership role. The series is intended to support CEOs on their AI journeys. https://www.deloitte.com/global/en/services/consulting/research/leading-a-generative-ai-fueled-enterprise.htmlhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/9c067181df/ir-9c067181dfSat, 17 Oct 2026 00:00:00 +0900academiaThere are growing concerns that AGI could pose catastrophic risks, so AGI companies need to substantially improve their risk management. This paper reviews popular risk assessment techniques from other safety-critical industries and suggests how AGI companies could use them. The authors note that these techniques alone will not be sufficient to assess catastrophic AI risks, but AGI companies should still review best practices from other industries. https://www.governance.ai/research-paper/risk-assessment-at-agi-companies-a-review-of-popular-risk-assessment-techniques-from-other-safety-critical-industrieshttps://pharma.intelligence-synthesis.com/en/ai-reports/s/9891cd4264/ir-9891cd4264Sat, 17 Oct 2026 00:00:00 +0900academiaWashington treats retaining AI dominance over China as both an economic and national security imperative, and has tightened export controls on AI chips and chipmaking equipment. The paper argues these measures are not enough and proposes a third pillar, strategic promotion, which means making American AI and compute the default choice in key international markets. This would involve financing compute infrastructure, providing training and technical assistance for AI adoption, and securing trade agreements that encourage reliance on trusted American AI. https://www.governance.ai/research-paper/export-controls-and-export-promotionhttps://pharma.intelligence-synthesis.com/en/ai-reports/s/9879483b26/ir-9879483b26Sat, 17 Oct 2026 00:00:00 +0900academiaThe article proposes a blueprint for auditing large language models (LLMs) in three layers: governance audits of technology providers, model audits of LLMs after pre-training but before release, and application audits of LLM-based applications. The authors argue these layers complement each other and can help manage some ethical and social risks. They also discuss the limitations of this approach and of auditing LLMs in general. https://www.governance.ai/research-paper/auditing-large-language-models-a-three-layered-approach