AI News Archive: July 30, 2026 — Part 5
Sourced from 500+ daily AI sources, scored by relevance.
- Pennsylvania town lists 43 specific demands to approve new AI data center project — developer calls local demands 'too difficult' as council slams response as 'approval by tantrum'
One township in Pennsylvania gave a specific list of demands for a data center developer to follow if they want to build their project in the area. Instead, they retracted their initial application and sent in a second one challenging the regulations.
- Why Dropbox refuses to pick a side in the ChatGPT-Claude-Gemini fight
Ask most people what Dropbox does, and they’ll tell you it’s where they store files. Ask Kenny Takeuchi, the company’s newly appointed VP of APJ Sales, and he’ll tell you that’s precisely the problem the tech firm is trying to move past. As ChatGPT, Claude and Gemini become the starting point for how knowledge workers […] The post Why Dropbox refuses to pick a side in the ChatGPT-Claude-Gemini fight appeared first on e27 .
Score: 52🌐 MovesJul 30, 2026https://e27.co/why-dropbox-refuses-to-pick-a-side-in-the-chatgpt-claude-gemini-fight-20260729/ - Science One Framework: A verifiable autonomous research framework via Chain-of-Evidence
General Science
- WEKA and Andromeda Partner to Power AI Workloads at Global Scale
WEKA and Andromeda Partner to Power AI Workloads at Global Scale The Straits Times
- BPO firm Teleperformance to open 1st Vietnam site as AI changes outsourcing
BPO firm Teleperformance to open 1st Vietnam site as AI changes outsourcing Nikkei Asia
- Data center backlash could slow CIOs’ AI plans
A growing backlash against building new data centers in the US may have huge cost implications for CIOs planning to expand their organizations’ AI initiatives. Protests against building new data centers were organized in 42 states in mid-July, with participants concerned about new facilities driving up electricity and water costs and using large swaths of land. As of mid-July, 10 states, including Florida, Georgia, and Virginia, had active data center construction moratoriums in place, and eight other states had pending legislation, according to datacenterbans.com . In addition, as of May, 23 states had approved large-load tariffs that require data centers to pay the full infrastructure cost for their facilities, says Arif Gasilov , a partner in the natural resources and built environment division of sustainability advisory firm Gasilov Group. IT leaders need to calculate the backlash into their planning for the compute and other IT infrastructure needs that new data centers would meet, he says. “What this means for CIOs is that power cost assumptions built in 2023 are wrong in close to half the country,” Gasilov says. “A CIO planning an AI deployment that depends on colocation or cloud capacity in any of these states should be asking their provider what the rate structure looks like under the new tariffs and recalculating economics.” In some cases, it may be possible to go smaller to avoid the moratoriums or tariffs on large data centers, but some state regulations target facilities close to each other as opposed to individual data centers, he notes. Deployment challenges If the backlash continues, IT leaders may need to rethink the way they deploy AI, says Chuck Girt , CTO at fiber-optic network provider FiberLight. With fewer options for AI compute power, organizations would have less flexibility in where they deploy AI workloads, he suggests. “I don’t think the rate of data center construction changes the direction AI is headed, but it could influence how organizations deploy and access AI at scale,” he says. “Most enterprises aren’t going to build this infrastructure themselves; they’re going to rely on cloud and data center environments to provide the compute AI requires.” A lack of data center options could put many organizations in a bind, says Kevin Surace , CEO of biometric security vendor TokenCore. “Compute capacity is becoming as strategically important as electricity, semiconductors, and network connectivity,” he says. “Fewer data centers mean less available capacity, reduced geographic redundancy, longer provisioning times, and greater dependence on a small number of cloud providers and locations.” Organizations that have not secured capacity could find that their AI strategy is technically sound but physically impossible to execute on schedule, he suggests. Surace, also an AI and green energy expert , is concerned that generalized fear about older data center designs is turning into blanket opposition to new construction. Modern facilities have cut down on the massive water use of older data centers, he notes, and some are using renewable energy generation. Nuclear power will become an electricity option soon, he adds. Cost pressures rising In the meantime, IT leaders should expect higher costs for compute and other IT infrastructure provided through data centers, Surace says. “Demand for AI compute is accelerating, so constraining the supply of facilities, electricity and high-density capacity will place upward pressure on cloud pricing, colocation, accelerator access, and long-term capacity contracts,” he adds. Organizations that have the capacity will should be able to protect themselves through multiyear agreements and dedicated infrastructure, he suggests. Smaller organizations, startups, and universities could face the greatest percentage increases and may simply be priced out of leading-edge AI capabilities, he adds. Therefore, Surace advises CIOs to treat compute and energy as strategic supply-chain risks. Organizations should secure capacity as soon as they can, avoid dependence on one cloud or one geographic region, and use smaller and more efficient AI models where appropriate, he recommends. He also suggests that CIOs ask data center providers several hard questions: Where does the water come from? Is the cooling loop closed? Who pays for new grid infrastructure? What percentage of power is generated onsite? What environmental monitoring is publicly reported? Data centers can mitigate some of the community concerns, he says. “Transparency and early community engagement are far less expensive than lawsuits, project cancellations, and moratoriums,” he adds. Backlash against inefficiency While protests are likely to continue, some don’t see the concerns about data centers as a condemnation of AI. Instead, the problem is with inefficient AI deployments, says Anurag Gurtu , cofounder and CEO of agentic AI platform provider Airrived. “Enterprises don’t actually want more data centers; they want more intelligence per watt, per GPU, and per dollar,” he says. “The winners won’t be those with the biggest infrastructure footprint, but those extracting the most value from every unit of compute.” Limitations on data centers will impact companies only if their AI strategies depend on nearly unlimited infrastructure, he adds. “The next generation of AI will be constrained by compute, power, and economics,” Gurtu says. “Organizations that optimize models, deploy domain-specific AI, and leverage hybrid architectures will continue to innovate, while those relying solely on scaling hardware will face diminishing returns.” While limited compute options could lead to higher prices, the solution is to focus on efficiency, he adds. “Rising infrastructure costs also accelerate innovation in model optimization, inference efficiency, and intelligent orchestration,” Gurtu says. “History shows constraints often become the catalyst for the next wave of breakthroughs.”
Score: 52🌐 MovesJul 30, 2026https://www.cio.com/article/4203074/data-center-backlash-could-slow-cios-ai-plans.html - Chinese Tech Companies Used to Benchmark Against America, but the World Model Field Has Broken That Pattern: WAIC Panel Says China Now Leads Without a US Counterpart to Follow
At WAIC 2026, Muka Robotics, Shengshu Technology, EvoPhys.ai, and Chengwei Capital discuss how Chinas world model startups now operate without US analogs, turning the conventional catch-up narrative.
- Inside India's AI boom: Data centres, energy and the infrastructure race
India's AI boom is fuelling a race to build data centres, expand electricity networks and strengthen digital infrastructure. Here's why these facilities matter, how they work and the challenges ahead
- SoFi expects big win from AI-powered financial coaching service
For once, it’s not about cutting jobs.
- Gemini’s notebook tools are catching up with the app that inspired them
Our APK teardown suggests website sources and mobile study tools may be on the way.
Score: 51🌐 MovesJul 30, 2026https://www.androidauthority.com/gemini-app-notebook-upgrades-apk-teardown-3693047/ - Amazon finds cases of AI causing runaway spending on tech projects
E-commerce giant’s staff said the new technology had caused budget overruns that sometimes took months to detect
Score: 51🌐 MovesJul 30, 2026https://www.ft.com/content/77baac40-d803-4084-94f3-a133653072cf?syn-25a6b1a6=1 - Meta and Microsoft's AI Spending: a Tale of Two Earnings Reports
Meta and Microsoft's AI Spending: a Tale of Two Earnings Reports Business Insider
Score: 51🌐 MovesJul 30, 2026https://www.businessinsider.com/meta-microsoft-ai-spending-tale-of-two-earnings-reports-2026-7 - Meta’s Case for Its AI Spending Keeps Getting Weaker
The company’s all-out splurge is running into higher costs, borrowing constraints and investor pushback.
Score: 51🌐 MovesJul 30, 2026https://www.wsj.com/tech/ai/metas-case-for-its-ai-spending-keeps-getting-weaker-aa4b9a5c?mod=rss_Technology - Reddit reports a solid quarter but shows signs of AI’s impact
Reddit's financial situation is looking good but uncertainty about its relationship to Google and the new AI-ified web are stirring market concerns.
Score: 51🌐 MovesJul 30, 2026https://techcrunch.com/2026/07/30/reddit-reports-a-solid-quarter-but-shows-signs-of-ais-impact/ - Zhongji slips in Hong Kong as AI selloff weighs on $6.8 billion debut
Zhongji slips in Hong Kong as AI selloff weighs on $6.8 billion debut Reuters
- Swiss startup AI Infrastructure Capital AG launches with €16 million to tackle AI compute bottleneck
AI Infrastructure Capital AG, a newly founded Swiss company that buys servers, runs them at sites with renewable power and rents the capacity out on long-term contracts, is launching with a recently closed funding round of around €16 million. Valyou investment foundation in Rapperswil is the round’s anchor investor, with its managing director Yonten Wagma […] The post Swiss startup AI Infrastructure Capital AG launches with €16 million to tackle AI compute bottleneck appeared first on EU-Startups .
- MoMo: Dial Motion Mode in Robot Manipulation with Spatiotemporal Action Tokenization
To operate effectively across diverse contexts, robots must not only perform manipulation tasks accurately but also adapt how their actions unfold to the task, object, and interaction setting. We ask whether this execution-level variation can be learned as a reusable behavioral factor shared across tasks. We present MoMo, a two-stage imitation-learning framework consisting of a spatiotemporal action tokenizer and a behavior-cloning transformer that takes task and a continuous motion-mode condition as inputs. Across six real-robot manipulation tasks, varying this condition produces steady…
Score: 50🌐 MovesJul 30, 2026https://machinelearning.apple.com/research/momo-motion-mode-manipulation - Compute Clusters Break Out Of National Labs To Scale AI
For compute-intensive applications, clusters of nodes that act as a single computer offer a way to scale performance and provide a workaround for organizations that lack access to leading-edge AI chips. The post Compute Clusters Break Out Of National Labs To Scale AI appeared first on Semiconductor Engineering .
Score: 50🌐 MovesJul 30, 2026https://semiengineering.com/compute-clusters-break-out-of-national-labs-to-scale-ai/ - Best Buy is selling an RTX 5080 for more than the RTX 5090’s MSRP
The Asus ROG Astral RTX 5080 OC now costs $2,099 at Best Buy, after launching at $1,499.
Score: 50🌐 MovesJul 30, 2026https://www.theverge.com/games/973173/asus-rog-rtx-5080-price-hike-best-buy - AI data centres and defence tech lead investment wave
Data centres, energy, and military technologies are the main investment channels tech buyers want to pour money into, according to new research. Law firm A&O Shearman’s latest outlook for technology investment said demand was growing for the infrastructure needed to build and run AI, while software companies faced greater scrutiny over whether AI could replace [...]
Score: 50🌐 MovesJul 30, 2026https://www.cityam.com/ai-data-centres-and-defence-tech-lead-investment-wave/ - AI for Trademark Search and Brand Protection
Explores how AI enhances trademark search and brand protection processes.
- Are investors really getting cold feet about the AI boom?
It is not clear whether there has been a serious change of heart about the trade underpinning the stock market
Score: 49🌐 MovesJul 30, 2026https://www.ft.com/content/00d91e68-9508-42bd-b1e3-124bf7dd390b?syn-25a6b1a6=1 - How avatarin built a 24/7 retail agent with GPT-Realtime
avatarin uses OpenAI’s GPT-Realtime to give Yamada Denki shoppers 24/7 multilingual support. In two weeks, 30,000 people used the agent and 92% of survey responses were positive.
- OpenAI to provide free ChatGPT access to researchers: What's in the plan?
OpenAI will provide free access to its frontier AI models to 100,000 researchers by 2027, alongside training, research support and collaboration tools for scientific discovery
- AI rewrites breach economics, hits BFSI and energy sectors hardest: Report
AI-enabled attacks are increasing breach costs as enterprise adoption outpaces governance, access controls and security safeguards, according to IBM and Kiteworks reports
- Parliament question asked if AI platforms get safe harbor. Here’s what MeitY said & what we think
Underlining that safe harbor for AI platforms depend on their nature of service and function, MeitY said the IT Act is "technology-neutral" & applicable to computer resources irrespective of the tech used. The post Parliament question asked if AI platforms get safe harbor. Here’s what MeitY said & what we think appeared first on MEDIANAMA .
- Google, RAI partner to drive digital adoption across over 600,000 retail storefronts
Google and the Retailers Association of India have partnered to accelerate digital adoption. This collaboration will focus on small and medium retailers across the country. They will leverage Google's product ecosystem for scalable digital solutions. The initiative aims to improve online discoverability and local reach for businesses. This partnership prepares retailers for the future of commerce through digital enablement.
- Labour forces through East End data centre despite local backlash
Labour forces through East End data centre despite local backlash telegraph.co.uk
Score: 49🌐 MovesJul 30, 2026https://www.telegraph.co.uk/business/2026/07/30/labour-forces-through-east-end-data-centre-despite-backlash/ - Sam Altman says cognitive atrophy is one of the most overlooked risks of the AI era
Sam Altman says cognitive atrophy is one of the most overlooked risks of the AI era Business Insider
Score: 49🌐 MovesJul 30, 2026https://www.businessinsider.com/sam-altman-ai-risk-cognitive-atrophy-brain-skills-openai-2026-7 - Companies are finally seeing AI ROI — and now they know how much more value it can deliver
Presented by SAP Enterprise AI has moved from experiment to execution, and that shift is beginning to show real returns. The SAP Value of AI Report 2026, produced with Oxford Economics and based on a survey of 2,600 business leaders across 13 countries, found that AI now supports nearly one-third of all tasks in the average organization, rising to 30% from 25% last year. ROI expectations for agentic AI have jumped from 10% last year to 17% this year, but many organizations believe AI could be delivering far more value. The report reveals that the gap comes down to strategy, data, and governance, rather than access to the newest model, says Sean Kask, chief AI strategy officer at SAP. "AI has moved from experiment to execution, and that's beginning to show real returns, but there's still a long way to go," Kask says. "That's because AI that lacks context, whether that's processes, data, or governance, at best creates activity without outcomes and at worst creates risk." Companies are still taking a piecemeal approach to AI Even as investment accelerates, more than half of organizations still invest in AI in an ad hoc or piecemeal way, and only 17% report a strategic, holistic approach to prioritization, though that figure has nearly doubled from 9% a year ago. That fragmentation may go back to board-level demands that employees start adopting AI without a strategy or adequate AI literacy behind it, which could produce scattered skunkworks efforts. In other companies, a lack of attention at board level can leave employees bringing their own tools to work and just experimenting. "You end up with a lot of organic, disjointed AI initiatives that pop up, and they struggled sometimes just because of data quality," Kask said. "But even the initiatives taking a strategic approach are still working in silos, where they may have consistent data that works in that one use case, but they're still not at the level where they're transforming an entire business process." That may help explain one of the report’s more counterintuitive findings: 69% of businesses say they are satisfied with their AI ROI, because they've proven AI can generate returns. Yet 67% remain unconvinced the technology is delivering its full potential, because that learning experience has made them aware of both how much more value AI can deliver and the challenges they need to overcome to scale it. Agents are changing the economics of enterprise AI SAP shipped more than 400 AI use cases across its portfolio so far, with many more in the works. Agents represent the next expansion, because they can plan and reason through multiple steps and tools to reach an objective, which mirrors how people and processes work, Kask says. "You're giving a task or an objective to an AI system, and it's able to iteratively work through several steps and access various tools to achieve that outcome," Kask said. "For instance, we've released, in beta, an agent for accruals accounting, a job that would typically take an accountant around 12 hours a month for a mid-size-company, and it gets reduced to two or three hours. So now scale that out across all these processes and its huge potential." In fact, general AI ROI went from 16% to 21% this year, and should grow to $15.9m in two years’ time, even as only 3% say they are fully prepared for it. Data quality remains the biggest barrier to AI value Getting ready for agents comes down to two fundamental requirements: connecting agents to contextually rich data, and governing them at scale. Data quality and availability are now the number-one reason organizations say they're not getting more value from AI, according to 73% of respondents, with 79% reporting rework, delays, or backlogs from low-quality outputs at least occasionally. The nature of the problem has changed compared to classic deep learning. Foundation models eliminate much of the need to find data, extract it, clean it, and train bespoke models, but they make preserving business context far more important. "As soon as you extract data from an ERP system, you break all the contextual information, all of the semantics, and for generative AI, that's the most useful part," Kask said. SAP is able to preserve that context at scale through a knowledge graph in its cloud ERP that maps 452,000 ABAP tables and 7.3 million data fields. In SAP Business Data Cloud, data products present information such as invoices and suppliers consistently across SAP and non-SAP systems without losing their business meaning. AI governance is the biggest challenge companies don't know they have As AI becomes more deeply embedded in business processes, governance is emerging as the next enterprise challenge. Only 12% of businesses say they are fully prepared to govern AI, while 69% acknowledge occasional to frequent use of unapproved shadow AI tools. “As companies roll out their AI initiatives, they often discover shadow agents – agents that can access data they shouldn’t or take actions they shouldn’t. The question then becomes: How do we audit these things?” Kask said. SAP’s AI Agent Hub responds by discovering and creating an inventory of agents, LLMs, and MCP servers, and customers have already surfaced thousands of SAP and non-SAP agents inside their landscapes that they did not know they had. It then layers on lifecycle management, identity and access control, and performance monitoring. Kask compares the discipline to hiring, since most companies would never onboard an employee without knowing which access rights and permissions that person needs to have in their role. Governance, however, extends beyond technology. Workforce transformation runs alongside the data work, with almost 80% of respondents agreeing that maximizing AI value requires more than technical upskilling and 75% already planning to reskill employees. The conversation is shifting away from which jobs AI will replace and toward how people and AI collaborate most effectively, since agents still require human oversight, redesigned workflows, and stronger judgment. All of this points toward what SAP calls the Autonomous Enterprise, which connects agents to contextually rich data and enterprise governance across functional silos while using Joule as the natural-language, generative interface between people and systems. “Realizing real value from AI is not going to be easy because it demands a new approach,” Kask concluded. “It is ultimately a human change more than a technical one, because you can only achieve real value if agents, processes, and people work as one.” Get the full findings. Download the SAP Value of AI Report 2026 . Sponsored articles are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. For more information, contact sales@venturebeat.com .
- Driving SA's transport into the intelligent era: Huawei launches 12 solutions across rail, road, ports, aviation
The rail, road, port and aviation technologies aim to support safer, more connected and efficient transport across South Africa.
- xAI upgrades Grok Voice with faster Think Fast 2 mode
xAI upgrades Grok Voice with faster Think Fast 2 mode YourStory.com
- AI supplier Innolight falls 10% after Asia's second-biggest listing of 2026
AI supplier Innolight falls 10% after Asia's second-biggest listing of 2026 Nikkei Asia
- 1 in 4 dollars spent on AI goes to waste, report finds
More than half of businesses lack a dedicated owner for artificial intelligence costs, which can lead to overspend, according to a Harness report.
- The AI industry is rallying around open models. Is it more than talk?
Welcome to AI Decoded, Fast Company ’s weekly newsletter that breaks down the most important news in the world of AI. I’m Mark Sullivan, a senior writer at Fast Company, covering emerging tech, AI, and tech policy. Sign up to receive this newsletter every week via email here . And if you have comments on this issue and/or ideas for future ones, drop me a line at sullivan@fastcompany.com, and follow me on X @thesullivan . The AI industry rallies around open models. Is it more than talk? Most of the big AI model makers keep the parameter weights, the billions of settings that work together to produce useful outputs, of their best models hidden from developers and other users. But this week, the AI industry has been falling all over itself to embrace models that expose those weights. On July 24, a coalition led by Nvidia, Microsoft, and Meta published “Open Weights and American AI Leadership,” a three-page letter asking Washington to avoid premature restrictions on downloadable models. Jensen Huang promoted it in his first post on X, and the list of signatories doubled to 50 within a day, adding OpenAI, Google, AMD, Cisco, and GitHub. Only Anthropic chose not to sign. The company’s CEO, Dario Amodei, wrote in a blog post Monday that Anthropic has never sought to ban open-weights models. But he argued that continuing to restrict the most powerful chips, most of which come from Nvidia, in places such as China is the right way to limit the creation of potentially dangerous AI models. He also advocated for the government to punish foreign model makers that use the outputs of Western AI models for large-scale training. Mark Zuckerberg took the open-weights argument to The Wall Street Journal on Tuesday, writing that superintelligent models are coming and that the defining question of our time is who gets access to them. Zuckerberg argues that it is better to distribute open models widely so developers can help make them safer. He also contends that allowing a few big tech companies, working closely with the government, to control powerful closed models is ultimately more dangerous. The irony is that Meta has largely given up on open models with the demise of its Llama line. The company is now placing its bets on massive closed models built by its new AI organization, Meta Superintelligence Labs, led by Alexandr Wang. Zuckerberg’s op-ed is being lauded across the AI industry, but it is also a perfect illustration of how cheap advocacy and good intentions can be. Meta’s new Muse Spark models are unlikely to become open-weights anytime soon. The economics of developing frontier AI models make closed weights increasingly inevitable. The work is hugely expensive, and investors such as Andreessen Horowitz, SoftBank, and Amazon, which are placing big bets on closed AI labs, will not earn the returns they want if the product is free and open to everyone. They want an AI market in which enterprises and startups depend on a handful of major providers that charge a premium for access to closed models. Until entirely new business models emerge that push Silicon Valley capital toward the development and distribution of open models, I will remain skeptical of the open-weights rah-rah from people such as Zuckerberg, Jensen Huang, and former Trump AI adviser David Sacks. For now, developers at enterprises and AI startups will continue choosing Chinese open-weights models such as Kimi 3 and DeepSeek V4 for most AI work, while reserving closed U.S. models from OpenAI and Anthropic for the hardest jobs. More than 1,100 AI workers call on Washington to ‘pace’ AI progress Bloomberg reports that more than 1,100 employees across nearly a dozen AI companies, including OpenAI, Anthropic, Google, and Meta, signed a petition urging the U.S. government to create a mechanism to “deliberately pace” AI development. The letter, titled “Pacing the Frontier,” was signed by Anthropic CEO Dario Amodei, OpenAI chief scientist Jakub Pachocki, Meta chief scientist Shengjia Zhao, and Google AI safety head Anca Dragan. It comes after OpenAI disclosed that two test models escaped a lab environment, reached the open internet, and breached another company’s internal system. Why Google DeepMind employees are depressed about slow progress in AI coding Axios reported last week that poor morale at Google DeepMind is contributing to delayed model releases, with Gemini 3.5 Pro reportedly several months behind schedule. One employee told the outlet that DeepMind has been slow to improve its models’ AI coding capabilities, a claim that a recently departed DeepMind researcher confirmed to Fast Company . The stakes extend beyond coding as a product category. AI coding agents increasingly help develop and improve the models themselves, and these tools have noticeably accelerated model releases at OpenAI and Anthropic. Google DeepMind cannot afford to fall further behind. Keeping pace will require a first-class AI coding tool. Nvidia may backstop a $500 billion OpenAI data center Nvidia is reportedly in talks to provide a financing guarantee of as much as $250 billion to help OpenAI lease a $500 billion, 10-gigawatt computing hub that SoftBank is developing in Ohio, with the site targeted for 2028. The backstop would let OpenAI raise construction and lease debt on Nvidia’s credit, which matters because OpenAI is unprofitable and cannot obtain an investment-grade rating on its own. AI investors’ chilly summer continues Investors continue to question how much Big Tech is spending on AI infrastructure. The impact is being felt mainly in the chip sector, which had seen strong growth much of this year. The Nasdaq 100 moved toward a correction Tuesday as the semiconductor selloff deepened. After a record high in late June, the Philadelphia Semiconductor Index had fallen 20% from that peak by Friday. Korea’s KOSPI index, which is dominated by memory chipmakers, had an up-and-down week last week and lost 5.72% of its value Friday. Pressure is building on the largest AI spenders to justify their capital budgets. Nvidia announced a major investment (reportedly $5 billion) in Ilya Stutskever’s Safe Superintelligence (SSI) Safe Superintelligence, the lab founded by former OpenAI chief scientist Ilya Sutskever, announced on Monday a long-term partnership with Nvidia that includes an undisclosed investment ( Bloomberg reports $5 billion) and access to Nvidia’s Vera Rubin platform. The agreement is expected to increase SSI’s compute resources by an order of magnitude. Bloomberg reported the equity commitment at $5 billion, one of the chipmaker’s largest funding deals of the AI boom. SSI has been a remarkably secretive company: You’ll find no leaks to the press about its operations, and it’s published no research or shipped any products since launching in 2024. SSI was last valued at $32 billion. More AI coverage from Fast Company: Claude users’ shared conversations were showing up in Google searches Meet the new robot dog patrolling LaGuardia Airport Should AI companies be able to outsource safety? OpenAI tells ChatGPT to stop impersonating famous authors Want exclusive reporting and trend analysis on technology, business innovation, future of work, and design? Sign up for Fast Company Premium.
- Tech giants see diverging results from the AI buildout
Samsung’s chipmaking division posted a 250-fold increase in quarterly operating profit, while Meta announced an $8 billion hit to the company’s free cash flow.
Score: 49🌐 MovesJul 30, 2026https://www.semafor.com/article/07/30/2026/samsung-meta-see-diverging-results-on-costs-of-ai-buildout - How an Australian AI scribe won over Canada’s doctors
Heidi’s Dr. Tom Kelly talks clinician-led adoption and scaling AI responsibly. The post How an Australian AI scribe won over Canada’s doctors first appeared on BetaKit .
Score: 49🌐 MovesJul 30, 2026https://betakit.com/how-an-australian-ai-scribe-won-over-canadas-doctors/ - Swedish legal AI unicorn Legora snaps up London-based Wexler in fifth acquisition of 2026
Legora, the Stockholm-based legal AI unicorn, has announced the acquisition of London-based Wexler, a fact intelligence platform that extracts, verifies, and reasons over the factual record from large and unstructured document sets. Wexler’s engineering team will make up the founding team of Legora’s London engineering hub. The company has been on an acquisition spree, with […] The post Swedish legal AI unicorn Legora snaps up London-based Wexler in fifth acquisition of 2026 appeared first on EU-Startups .
- First look: Gemini could soon help you set up your new Android phone
Google is working on an AI-powered setup assistant that offers suggestions and allows you to ask questions.
Score: 48🌐 MovesJul 30, 2026https://www.androidauthority.com/google-gemini-android-setup-assistant-apk-teardown-3692815/ - South Korea’s women web sleuths fight AI deepfake porn
South Korea’s women web sleuths fight AI deepfake porn The Japan Times
Score: 48🌐 MovesJul 30, 2026https://www.japantimes.co.jp/news/2026/07/30/asia-pacific/crime-legal/korea-women-ai-deepfake-porn/ - Korea has two-year window to boost autonomous driving: Analysis
Korea has two-year window to boost autonomous driving: Analysis 매일경제
- Ready Server Pilots Full-Immersion Cooling to Prepare Singapore Facility for AI-Ready Compute Services
Ready Server Pilots Full-Immersion Cooling to Prepare Singapore Facility for AI-Ready Compute Services The Straits Times
- Run High-Performance Core Math at Scale with NVIDIA nvmath-python
NVIDIA nvmath-python is a library designed to bridge the gap between the Python scientific community and NVIDIA CUDA-X math libraries. It gives Python users...
Score: 48🌐 MovesJul 30, 2026https://developer.nvidia.com/blog/run-high-performance-core-math-at-scale-with-nvidia-nvmath-python/ - Gemini Spark can now use Chrome to auto browse, AI Pro access goes international
Gemini Spark is getting two big updates today, starting with Chrome auto browse integration on desktop.
- GoKwik and PayU bring multi-brand D2C shopping to ChatGPT, launch AI-powered commerce experience
Hyphen, Beardo and Kilrr among the first brands onboard as companies introduce conversational shopping with integrated payments The post GoKwik and PayU bring multi-brand D2C shopping to ChatGPT, launch AI-powered commerce experience appeared first on Express Computer .
Score: 48🌐 MovesJul 30, 2026https://www.expresscomputer.in/news/gokwik-payu-chatgpt-d2c-commerce/137222/ - LangSmith LLM Gateway: runtime controls for production agents
Runtime controls for production agents using LangSmith LLM Gateway.
Score: 48🌐 MovesJul 30, 2026https://blog.langchain.dev/blog/langsmith-llm-gateway-runtime-controls-for-production-agents - Finance firms set to pour more investment into AI amid ‘data divide’ fears
A majority of surveyed global asset management firms plan to raise their artificial intelligence budgets by at least 50 per cent within the next year as the technology transforms the finance industry, a recent study showed. The study, released Tuesday by US fintech firm Clearwater Analytics, indicated the adoption of AI will have a major impact on labour-intensive operations. Of the fund managers polled, 62 per cent said they expected transformative change in data generation and...
- Language models can't spark scientific revolutions, but world models might
Can language models spark a scientific revolution? In a position paper titled "LLMs can't jump," Google Deepmind's Tom Zahavy argues they can't. They're missing the cognitive mechanism needed to create something truly new. The article Language models can't spark scientific revolutions, but world models might appeared first on The Decoder .
Score: 48🌐 MovesJul 30, 2026https://the-decoder.com/language-models-cant-spark-scientific-revolutions-but-world-models-might/ - Southeast Asia in the 2026-2030 world order: Trade, chips, AI, and capital
Southeast Asia is not entering the second half of the decade as a spectator to global change. It is becoming one of the places where that change will be absorbed, negotiated, and in some cases redirected. For founders and business leaders, the implication is simple but uncomfortable: the rules that shaped regional growth over the […] The post Southeast Asia in the 2026-2030 world order: Trade, chips, AI, and capital appeared first on e27 .
Score: 48🌐 MovesJul 30, 2026https://e27.co/southeast-asia-in-the-2026-2030-world-order-trade-chips-ai-and-capital-20260728/ - What are Flock cameras and why are they so controversial?
Flock cameras photograph passing vehicles and help police track cars. Here’s how they work and why communities are pushing back.