AI News Archive: June 11, 2026 — Part 2
Sourced from 500+ daily AI sources, scored by relevance.
- OpenAI Execs Are Panicking
They're getting desperate. The post OpenAI Execs Are Panicking appeared first on Futurism .
Score: 79🌐 MovesJun 11, 2026https://futurism.com/artificial-intelligence/openai-execs-panicking-price-anthropic - Chinese agents caught rebuilding botnets and stirring the pot on AI datacenter debate
PRC eyes are watching you
- Dallas influencer sues underwear maker over AI deepfakes that show her partially nude
Dallas influencer sues underwear maker over AI deepfakes that show her partially nude Dallas News
Score: 79🌐 MovesJun 11, 2026https://www.dallasnews.com/business/article/dallas-influencer-sues-intimate-apparel-maker-22301850.php - Grok Is Still Hosting Sexualized Deepfakes of Famous Women
A WIRED investigation found dozens of “nudified” deepfake images and videos on Grok's website, including nonconsensual depictions of celebrities and at least one prominent US politician.
Score: 79🌐 MovesJun 11, 2026https://www.wired.com/story/grok-is-still-hosting-sexualized-deepfakes-of-famous-women/ - Anthropic Pursues First Data Center Leases, Seeks Financial Backing From Google
Anthropic Pursues First Data Center Leases, Seeks Financial Backing From Google The Information
- Kids Increasingly Use AI for Tutoring, Emotional Support
According to a survey of 1,204 children by Common Sense Media, about half reported using AI weekly, and 42 percent of those who said they use AI frequently also said it would be tough to stop using it.
Score: 78🌐 MovesJun 11, 2026https://www.govtech.com/education/k-12/kids-increasingly-use-ai-for-tutoring-emotional-support - AI is now a geopolitical asset. African presidents are racing to catch up.
Only a few years ago, AI policy on the continent revolved around ethics, digital literacy and startup incubation. Now governments are discussing cloud infrastructure, sovereign data, regional computing capacity and local language models, subjects once confined to engineers and Silicon Valley executives.
Score: 78🌐 MovesJun 11, 2026https://techcabal.com/2026/06/11/african-presidents-are-now-racing-ai-infrastructure/ - Open-source artificial intelligence is reshaping the future of humanity: Scientists question, if the world is ready
Open-source artificial intelligence is reshaping the future of humanity: Scientists question, if the world is ready EurekAlert!
- Boston College creates Krantz Institute for AI with gift from Definitive Healthcare owner
To Provost David Quigley, AI needs to be confronted and discussed by every student at Boston College. And a new AI institute at the school is the perfect home base for provocative thought.
Score: 78🌐 MovesJun 11, 2026https://www.bizjournals.com/boston/news/2026/06/11/boston-college-launches-ai-institute.html?ana=brss_6150 - SpaceX’s 1M AI Satellites Will Create Space Junkyard, Experts Warn
As Musk prepares for the largest IPO in history, SpaceX's plan to park a million data centers in Earth’s orbit has left scientists worried about a Wall-E-style orbital graveyard.
Score: 78🌐 MovesJun 11, 2026https://www.cnet.com/science/space/space-x-one-million-ai-satellite-space-junkyard/ - NVIDIA and SK hynix announce multi-year technology partnership to advance memory for AI Factories
NVIDIA and SK hynix have announced a multi-year technology partnership to advance next-generation memory for the global AI factory buildout and accelerate semiconductor design and manufacturing. The agreement builds on years of deep co-engineering collaboration that has powered some of the world’s most advanced AI computing platforms. “AI factories are the engines of the next industrial revolution, and advanced memory is essential to their performance,” said Jensen Huang, Founder and CEO of NVIDIA. “SK hynix has been an extraordinary partner to NVIDIA, playing a central role in delivering advanced memory technologies for NVIDIA AI computing platforms. Together, we will codevelop the next generation of memory for AI factories and support the accelerating global expansion of AI infrastructure — from frontier model training to agentic and physical AI.” “SK hynix and NVIDIA have been building toward this for years, and this partnership reflects the depth of that collaboration,” said Chey Tae-won, Chairman of SK Group. “Together, we are codeveloping the next generation of memory for AI factories and applying AI to how we design and manufacture semiconductors — work that will shape the future of AI infrastructure.” The multi-year agreement supports supply to address the extended development cycles of advanced memory. As AI factories scale globally, this strategic partnership enables memory supply to keep pace with NVIDIA’s infrastructure roadmap and the sustained buildout of AI infrastructure worldwide. Through this partnership, SK hynix will diversify into new markets NVIDIA is creating — spanning AI infrastructure, personal AI and physical AI — codeveloping memory for NVIDIA Vera Rubin AI supercomputers, NVIDIA Vera CPUs, NVIDIA RTX Spark-powered PCs and NVIDIA Jetson Thor robotic computing platforms. Accelerating technology CAD and semiconductor simulation SK hynix is using NVIDIA CUDA-X libraries and AI to speed semiconductor simulation, including technology computer-aided design and computational lithography workflows. SK hynix is also using CUDA-X and the NVIDIA PhysicsNeMo framework to deliver core-workload acceleration across its in-house simulation codes and AI physics workflows. By extending these tools to the semiconductor electronic design automation and simulation ecosystems, this initiative paves the way for three-way collaborations among chipmakers, NVIDIA and electronic design automation software vendors. Advancing fab digital twins for autonomous manufacturing SK hynix is developing fab digital twins as a foundation for autonomous fab operations. Teams can use scene optimization technologies, as well as NVIDIA Omniverse libraries and OpenUSD pipelines, to build 3D factory scenes for visualizing, simulating and optimizing complex semiconductor manufacturing environments. These digital twins can also support operational optimization, including the movement of autonomous mobile robots and other fab assets, using the open source, GPU-accelerated NVIDIA cuOpt decision optimization engine and the NVIDIA Metropolis platform. The companies are also exploring ways to connect digital twins with existing legacy software and agentic AI workflows, enabling AI systems to reason over fab data, automate tasks and improve manufacturing decision-making.
- Ashwini Vaishnaw calls for a new AI Law, reversing MeitY’s own position and his 2023 Parliamentary reply
India's IT Minister Ashwini Vaishnaw signals need for a new AI law, contradicting earlier government stances, while addressing Mythos access, deepfake concerns, and AI-driven job displacement. The post Ashwini Vaishnaw calls for a new AI Law, reversing MeitY’s own position and his 2023 Parliamentary reply appeared first on MEDIANAMA .
- Context compression finally works in production: new research cuts LLM input 16x without the accuracy hit
Context windows are becoming a computational bottleneck. The longer an agent runs, the more tokens accumulate from retrieved documents, reasoning traces and conversation history, and the more memory and compute that growing context demands. Most existing solutions either degrade model accuracy, require the full context to load before compression begins, or produce memory savings that don't translate into real speedups in standard serving infrastructure. A research team from NYU, Columbia, Princeton, University of Maryland, Harvard and Lawrence Livermore National Laboratory published a paper this week that proposes a novel fix. The researchers introduce the concept of Latent Context Language Models, or LCLMs, a family of encoder-decoder compression models that compress input context before it reaches the decoder. The models are open-sourced on HuggingFace. Unlike KV cache compression methods — the dominant approach in the field, which still materialize the full KV cache before evicting entries — LCLMs compress the input token sequence before decoder prefill, so higher compression ratios directly reduce decoder-side compute and memory. The paper reports LCLMs at 16x compression produced output 8.8 times faster than KV cache baselines on the RULER long-context benchmark. "These ballooning contexts take up memory and compute, and they are becoming a computational bottleneck for LLMs," Micah Goldblum, co-lead advisor on the project and a researcher at Columbia University, told VentureBeat. "Our goal was to train language models end-to-end that can handle very long contexts efficiently and accurately. If you can make such a language model, everything becomes cheaper and faster." What LCLMs can do LCLMs let models process much longer contexts than would otherwise be practical, at a fraction of the memory and compute cost, without the accuracy degradation that makes most compression methods a poor tradeoff in production. At 4x compression, the paper reports accuracy of 91.76% on the RULER benchmark, compared to 94.41% with no compression at all. That is less than a 3 point drop for cutting context to a quarter of its original size. At 16x compression, where 93.75% of input tokens are removed, accuracy fell to 75.06%. Every KV cache method tested at the same compression ratio scored lower. The gains hold on shorter inputs too. On GSM8K math word problems, where the full prompt is compressed rather than just retrieved documents, LCLMs outscored every other method tested regardless of compression ratio. How it was built The architecture pairs a 0.6B encoder with a 4B decoder. The encoder compresses blocks of input tokens into shorter sequences of latent embeddings. The decoder processes those in place of the original tokens. Training ran across more than 350 billion tokens. The training recipe mixes three data types: Continual pre-training data with compressed and uncompressed spans interleaved throughout Supervised fine-tuning data covering reasoning and long-context tasks An auxiliary reconstruction task that pushes the encoder to retain fine-grained detail The combination addresses a tradeoff that limited earlier compression work, where preserving reconstruction accuracy came at the cost of general task performance. An architecture search identified the optimal configuration. The paper found that scaling the decoder matters more than scaling the encoder. Where it fits in an agentic stack An LCLM is not an abstract research concept. It is designed to work with an existing stack. "You can simply swap out LCLMs for any existing LLM," Goldblum said. "Whenever you retrieve data such as documents and want to dump it into your model's context, simply run those documents through the LCLM's compressor first." He noted that in the research paper, the researchers demonstrated how to build agents that selectively decompress useful text. "Think about this like a human skimming content before zooming in on relevant details," Goldblum said. Goldblum also cautioned that teams integrating the approach into existing agentic pipelines will need to tune their RAG systems accordingly. "We also haven't worked on online compression of reasoning traces," he said. "The naive approach of just occasionally compressing the trace while generating it might work, but that remains to be determined." What this means for enterprises Context windows are growing faster than inference infrastructure can keep up, and enterprises are already spending to fix it. VB Pulse Q1 2026 survey data from 100-plus employee organizations shows hybrid retrieval adoption intent tripling from 10.3% in January to 33.3% in March. Retrieval optimization overtook evaluation as the top investment priority by March, reaching 28.9% of qualified respondents. Three things stand out for teams evaluating production fit: Inference cost scales with context length. At 1 million tokens, uncompressed inference with standard KV cache methods runs out of memory on a single H200 GPU. The paper reports LCLMs at 16x compression remain within memory bounds at that context length. RAG pipeline integration requires tuning. Teams with existing RAG pipelines will need to validate compression behavior against their retrieval quality metrics before deploying at scale. Reasoning trace compression is unsolved. For agents running long reasoning chains, context growth from the trace is a separate problem from document retrieval. Goldblum acknowledged the gap directly: the naive approach of periodic trace compression might work but has not been tested. The models are available at huggingface.co/latent-context and the code at github.com/LeonLixyz/LCLM. "The biggest things our architectures do is give your model access to much larger contexts, but they also unlock multiscale approaches where your model can skim vast amounts of text or code super fast and then only zooms in and fully reads a small portion of the most useful text," Goldblum said.
- Why Microsoft and Other Anthropic Customers Held Off On Using Claude Fable
Why Microsoft and Other Anthropic Customers Held Off On Using Claude Fable The Information
Score: 78🌐 MovesJun 11, 2026https://www.theinformation.com/newsletters/ai-agenda/microsoft-anthropic-customers-held-using-claude-fable - Amazon Says Its Data Centers Used 2.5 Billion Gallons of Water in 2025
The company said water use at sites it owns and operates directly fell 2% from 2024 levels, even while it expanded its data-center footprint.
- Tesla's Optimus robot ambitions come into focus in Austin
Tesla's Optimus robot ambitions come into focus in Austin Austin American-Statesman
Score: 77🌐 MovesJun 11, 2026https://www.statesman.com/business/article/tesla-optimus-factory-gigafactory-texas-22291045.php - Hackers Exploit Langflow Vulnerability for Remote Code Execution
Disclosed in March, the security defect enables unauthenticated attackers to write files to arbitrary locations on the system. The post Hackers Exploit Langflow Vulnerability for Remote Code Execution appeared first on SecurityWeek .
Score: 77🌐 MovesJun 11, 2026https://www.securityweek.com/hackers-exploit-langflow-vulnerability-for-remote-code-execution/ - CISA Warning: LiteLLM Flaw Could Expose Enterprise AI Gateways
CISA’s LiteLLM warning shows why AI gateways and agents need service account governance, scoped access, credential rotation, and audit trails. The post CISA Warning: LiteLLM Flaw Could Expose Enterprise AI Gateways appeared first on TechRepublic .
Score: 77🌐 MovesJun 11, 2026https://www.techrepublic.com/article/news-litellm-cisa-ai-gateway-service-account-governance/ - PepsiCo expanding autonomous truck use in its supply chain
The multiyear deal with Gatik will help the food and beverage giant increase capacity in "hard to staff" areas of its transportation network.
Score: 77🌐 MovesJun 11, 2026https://www.supplychaindive.com/news/pepsico-expanding-autonomous-truck-use-in-its-supply-chain/822403/ - OpenAI to acquire Ona
OpenAI plans to acquire Ona to expand Codex with secure, persistent cloud environments, enabling long-running AI agents across enterprise workflows.
- Oracle reports record revenue and profit — and $24 billion of negative cash flow from the AI race
Oracle Corp. released its 2025-26 fiscal year results June 10: record revenue, record profit and also record spending that resulted in negative free cash flow. All of that is happening while the tech company makes headway on the initial infrastructure for its future East Bank office campus.
Score: 76🌐 MovesJun 11, 2026https://www.bizjournals.com/nashville/news/2026/06/11/oracle-full-year-earnings-report.html?ana=brss_6150 - AI Is Scaling Healthcare Costs Because the System Was Built That Way
AI Is Scaling Healthcare Costs Because the System Was Built That Way MedCity News
Score: 76🌐 MovesJun 11, 2026https://medcitynews.com/2026/06/ai-is-scaling-healthcare-costs-because-the-system-was-built-that-way/ - Einride begins trading on Nasdaq after completing de-SPAC
Einride began trading on Nasdaq after completing its de-SPAC. The company is scaling both electric trucks and cabless autonomous vehicles. The post Einride begins trading on Nasdaq after completing de-SPAC appeared first on FreightWaves .
- IBM, ServiceNow team to bring AI to legacy enterprise systems
IBM and ServiceNow are teaming up for new services they say will help enterprise customers bring aging legacy environments into an AI-ready infrastructure. The collaboration will combine IBM’s AI, data, and automation capabilities and ServiceNow’s AI platform for a variety of offerings that will modernize aging systems, enable autonomous IT operations, and help organizations evolve existing systems rather than replace them, the companies stated. ServiceNow says its AI-Platform offers a workflow layer that sits on top of an enterprise’s existing systems and helps automate work across them. Decades of deeply interconnected legacy systems are the biggest barrier to moving fast on AI, the companies stated . Their pairings will take advantage of Big Blue’s expertise in working with large systems, such as its mainframe environment , and extensive legacy applications, along with ServiceNow’s workflow and agent management platforms. “Most enterprises have the ambition to deploy agentic AI, but lack the foundation to run it at scale,” said John Aisien, senior vice president and general manager, central product management, security and risk, at ServiceNow. “IBM brings the tooling to modernize the systems and extend ServiceNow’s data capabilities. ServiceNow provides the platform to put that data to work across every workflow in the business.” The vendors will focus on three core services that will be available in the second half of 2026: Application modernization : Scans and refactors legacy systems using tools like IBM Bob, Enterprise Application runtime (Java) and IBM watsonx.data to help enterprises bring existing applications into the AI era without starting from scratch. Autonomous infrastructure operations : Integrates Red Hat Ansible, IBM Bob, Instana, Hashicorp Terraform, and Hashicorp Vault into ServiceNow IT workflows to detect, remediate, and resolve issues before they affect the business. Data governance : Extends ServiceNow Workflow Data Fabric with IBM watsonx.data to unlock key capabilities like Data Quality, Observability, Master Data Management – employing the ServiceNow Data Catalog so that mutual customers can keep track of their AI-ready data. IBM and ServiceNow have a long-standing relationship , having worked together to help large enterprise customers implement everything from cloud computing, automation, and security to IT service management and observability technologies.
Score: 76🌐 MovesJun 11, 2026https://www.networkworld.com/article/4184195/ibm-servicenow-team-to-bring-ai-to-legacy-enterprise-systems.html - Healthcare costs poised to jump 9% in 2027 as health plans blame AI adoption, drug prices
Health plans are projecting the highest medical cost trend in nearly two decades in 2027, with commercial health costs expected to rise 9%, according to a new analysis from PwC.
- Amazon touts water savings amid data center pushback
Amazon says its data centers use water more efficiently than the industry average and is urging others to improve as scrutiny of data centers intensifies. Why it matters: Water use has emerged as one of the biggest pressure points in the AI data center buildout, pushing companies like Amazon to publicly defend their efforts. Driving the news : Amazon revealed Thursday it was 75% of the way toward its 2030 goal — first set in 2022 — to replenish more water into communities with its data centers than it's consuming. The tech giant also said its data centers are seven times more water-efficient than the industry average. Friction point : Roughly 70% of Americans oppose building data centers in their communities, with water use for cooling and other environmental concerns ranking as the top reason, according to Gallup polling released in May. State of play: Amazon's announcement — following a similar water-focused push from Google last week — shows how major tech companies are increasingly trying to address public concern over the environmental toll of the AI buildout. "There is a perception, perhaps, that the data centers are taking more water than people understand," said Kara Hurst, chief sustainability officer at Amazon, in an interview. "I do think it's incredibly important that we are transparent." Hurst said it should be a "race to the top" with efficient water use across the industry. The fine print: Amazon's "industry average" is not a directly reported industry benchmark. It's based on a January academic study and converted using a standard Energy Department methodology . Between the lines: Hurst made an argument that Google executives also made last week: data centers use far less water compared to other industries, including agriculture and household lawn watering. Reality check: Comparisons to other industries may do little to ease concerns in communities facing a rapid influx of large data center projects. Hurst acknowledged that Amazon is planning for more growth overall. "We are growing," Hurst said. "We want it to be good growth, sustainable growth." Case in point: In Northern Virginia, one of its largest data center regions, the company said it reduced water use by 42% in 2025 compared to 2024, "even as demand for computing continued to grow." How it works: Data centers must continuously remove heat generated by computing equipment. Companies increasingly use liquid-cooling systems to cool the hottest AI chips, typically circulating coolant through sealed systems that require little ongoing water use. More water is often used to remove heat from the facility itself. Operators generally balance water consumption against electricity consumption when choosing cooling methods. Amazon says it relies heavily on "free-air" cooling, which uses outside air when conditions allow and reduces the need for water-intensive cooling. Yes, but: Like Google did last week, Amazon argues that on the hottest days, using water can be the most efficient option overall. "We determined it's better overall to use some water during the hottest days of the year than to overconsume electricity during the very moments when the grid is most stressed," its press release states. What we're watching: The key question is whether efficiency gains can offset overall growth. Even as companies reduce water use per unit of computing, total demand for AI infrastructure continues to surge.
- ByteDance Spins Off AI Drug Discovery Business for Independent Financing, AI4S Enters Industrial Phase
ByteDance is spinning off its AI drug discovery business for independent financing, retaining majority control as the company commercializes its AI capabilities in life sciences.
- Inside Jamnagar: How Meta and Reliance are building India’s AI infrastructure backbone
Meta and Reliance Industries are expanding their partnership beyond connectivity to build an AI-enabled data centre in Jamnagar, Gujarat, marking a major step in India’s AI infrastructure journey. The collaboration underscores India’s growing role as a global AI hub while placing sustainability and renewable energy at the centre of the next wave of digital growth.
- Siri AI is powered by Gemini models, but is not Gemini – what does that mean?
We know that Siri AI and other Apple Intelligence features are powered by Google’s Gemini models, but Apple has been at pains to point out that this is not the same as running Gemini on iPhone. While there are still some unknowns, a far clearer picture is emerging about exactly what all of this means …
Score: 76🌐 MovesJun 11, 2026https://9to5mac.com/2026/06/11/siri-ai-is-powered-by-gemini-models-but-is-not-gemini-what-does-that-mean/ - SK Group plans AI factory in Japan for 2028-2029
Japan also has strong positions in chip materials and equipment, including about 88% of the global coater-developer market and 53% of silicon wafers.
Score: 75🌐 MovesJun 11, 2026https://www.techinasia.com/sk-group-taps-younger-leaders-in-ai-focused-reshuffle - Japan financial firms to join NEC-Anthropic AI collaboration
Japan financial firms to join NEC-Anthropic AI collaboration The Japan Times
Score: 75🌐 MovesJun 11, 2026https://www.japantimes.co.jp/business/2026/06/11/japan-banks-nec-collaboration/ - AI-powered Siri: Can 'understand' images and describe visual content — 9 things users need to know
AI-powered Siri: Can 'understand' images and describe visual content — 9 things users need to know Gulf News
- Anthropic is spending $150 million to embed 1,000 AI fellows inside nonprofits. No degree required.
Anthropic is donating $150 million to place 1,000 AI fellows inside nonprofit organisations across the United States. The programme, called Claude Corps, will pay early-career workers $85,000 plus benefits for a year-long placement where they help nonprofits use Claude more effectively. Applications opened Wednesday and close on July 17. No college degree is required. Applicants […] This story continues at The Next Web
Score: 75🌐 MovesJun 11, 2026https://thenextweb.com/news/anthropic-claude-corps-150m-nonprofit-fellowship - John R. Dearie: America needs a consistent national approach to AI regulation
John R. Dearie: America needs a consistent national approach to AI regulation Chicago Tribune
Score: 75🌐 MovesJun 11, 2026https://www.chicagotribune.com/2026/06/11/opinion-us-ai-regulation-illinois/ - McKinsey Consultants Are Letting New Technology Take Over an Essential Part of Their Work
McKinsey Consultants Are Letting New Technology Take Over an Essential Part of Their Work entrepreneur.com
Score: 75🌐 MovesJun 11, 2026https://www.entrepreneur.com/business-news/mckinsey-consultants-are-letting-ai-take-over-their-work - Google DeepMind is worried about what happens when millions of agents start to interact
Google DeepMind is funding research into the potential dangers of situations where millions of different AI agents interact with each other online. According to Rohin Shah, who directs the company’s AGI safety and alignment research, the mass-market arrival of agents that can carry out tasks without human oversight and follow instructions given to them by other…
- Coinbase launches tool to let AI agents manage trading and payments
Coinbase is betting that AI agents will become the primary interface for people's financial activity.
Score: 75🌐 MovesJun 11, 2026https://www.cnbc.com/2026/06/11/coinbase-launches-tool-to-let-ai-agents-manage-trading-and-payments.html - Dubai to support 295,000 companies with Agentic AI under new Sheikh Hamdan-backed plan
Dubai to support 295,000 companies with Agentic AI under new Sheikh Hamdan-backed plan Arabian Business
- Why AI-driven threats are exposing the limits of MSP security stacks
AI-driven attacks are exposing the limits of fragmented MSP security stacks and slow response workflows. Kaseya breaks down why integrated security, automation, and recovery are becoming essential. [...]
- Why Anthropic CEO Dario Amodei wants AI regulated like aviation and pharma
Anthropic chief Dario Amodei says advanced AI now poses public safety and national security risks, calling for mandatory testing and government oversight before deployment
- China races against US for AI’s holy grail: self-improving tech
British mathematician Jack Good coined the term “intelligence explosion” 61 years ago to describe what would happen when an intelligent machine entered a runaway cycle of fully automated self-improvement, quickly leaving human intelligence far behind. For decades, that hypothetical capability – often described as “recursive self-improvement” (RSI) – has been seen as AI’s holy grail. The logic goes that the first country or company to achieve RSI would leave its competitors in the dust, cementing...
- Anthropic CEO Dario Amodei wants AI models regulated like airplanes
Anthropic CEO Dario Amodei has said there is a stricter need for regulation around AI, similar to how Airplanes are regulated.
- Google: 3.5M users have tested the Gemini for Home assistant, Speaker teased for next week
Google sent an email to customers today thanking Gemini for Home early access testers for their feedback, and laying the groundwork for the upcoming Google Home Speaker.
- Kuwait joins AI infrastructure race with $10B venture
Kuwait’s sovereign wealth fund is backing a new AI infrastructure venture alongside KKR, Nvidia, and power company Vistra.
Score: 75🌐 MovesJun 11, 2026https://www.semafor.com/article/06/11/2026/kuwait-joins-ai-infrastructure-race-with-10b-venture - Jeff Bezos Wants to Build an ‘Artificial General Engineer’
As co-chief executive of the start-up Prometheus, the Amazon founder is using A.I. to improve how devices ranging from computers to jet engines are made.
Score: 75🌐 MovesJun 11, 2026https://www.nytimes.com/2026/06/11/technology/bezos-prometheus-ai-engineer.html - How a Google DeepMind Spinoff Hunts Hidden Drug Targets
Isomorphic Labs is developing a new engine for AI drug discovery
- Mastercard partners with Chicago startup to support autonomous AI transactions
Coinflow is among several fintech startups working with Mastercard on Agent Pay for Machines, a product designed to let AI agents complete purchases autonomously.
Score: 75🌐 MovesJun 11, 2026https://www.bizjournals.com/chicago/news/2026/06/11/mastercard-startup-coinflow-fintech-ai.html?ana=brss_6150 - OpenAI could go from AI pioneer to AI's BlackBerry, says Forrester
As OpenAI courts investors and chases enterprise customers, Forrester says today's AI leader could become tomorrow's cautionary tale
- How artificial intelligence is redefining car design and the future of factory work
How artificial intelligence is redefining car design and the future of factory work Automotive News
Score: 74🌐 MovesJun 11, 2026https://www.autonews.com/events/congress/ane-congress-ai-car-design-changes-factory-work-0611/ - Agentic AI Is Changing Data Center Architectures
Standalone GPUs are being replaced by heterogeneous SoCs and chiplets that combine CPUs, GPUs, and NPUs to eliminate memory bottlenecks, reduce latency, and boost efficiency. The post Agentic AI Is Changing Data Center Architectures appeared first on Semiconductor Engineering .
Score: 74🌐 MovesJun 11, 2026https://semiengineering.com/agentic-ai-is-changing-data-center-architectures/