AI News Archive: July 12, 2026 — Part 1
Sourced from 500+ daily AI sources, scored by relevance.
- What are Copilot+ PCs? Everything you need to know
Copilot+ PCs promise smarter Windows search, local AI tools, and longer battery life, though the badge comes with strict hardware rules and several important caveats.
- WATCH: Humanoid robots step up to the operating table
ABC News' Leslie Lopez gets an inside look at "Surgie," a robot guided by surgeons during real operations that could become a future game changer for hospitals.
- Claude Code now has a built-in browser that lets the AI read, click, and type on external websites
Claude Code now has a built-in browser that lets the AI open, read, and interact with web pages directly inside the development environment. Write actions on external sites are screened by classifiers, and purchases or account creations need user approval. The article Claude Code now has a built-in browser that lets the AI read, click, and type on external websites appeared first on The Decoder .
- The Apple Car may be dead, but it became the foundation of Apple Intelligence
Apple's canceled self-driving car project reportedly became the technological foundation for Apple Intelligence, helping create the Neural Engine and the AI hardware powering today's iPhones, Macs, and Apple AI servers.
Score: 90🌐 MovesJul 12, 2026https://www.digitaltrends.com/cars/the-apple-car-may-be-dead-but-it-became-the-foundation-of-apple-intelligence/ - AI has triggered the biggest gas-plant building boom in history, and a quiet fight to stop it
The AI build-out has done something the fossil-fuel industry could not do for itself. It has set off the largest-ever construction boom in natural gas-fired power plants, the Associated Press reports. Aging coal plants are being kept alive past their retirement dates too. Utilities, plant owners, and the federal government have all pushed to postpone the […] This story continues at The Next Web
Score: 89🌐 MovesJul 12, 2026https://thenextweb.com/news/ai-data-centres-gas-plants-clean-energy-fight - OpenAI is hiring to build ChatGPT for families. Here's what we know
OpenAI is hiring a product manager to develop AI experiences for families, caregivers, and older adults.
- Why the Trillion-Dollar AI Buildout Is Quietly Squeezing Small-Business Owners
New York Fed President John Williams says AI-driven demand is now one of the inflation risks he is watching most closely. The stakes are high for small-business owners.
Score: 87🌐 MovesJul 12, 2026https://www.inc.com/georgia-fearn/trillion-dollar-ai-buildout-quietly-squeezing-small-business-owners/91372060 - While Neuralink drills into skulls, China’s BrainCo is betting brain tech will be something you wear
The most visible race in brain-computer interfaces involves surgery. But one of China’s most valuable neurotech firms is deliberately not competing in it, CNBC reports. BrainCo, based in Hangzhou, builds devices that read the brain from outside the skull. Headbands and caps pick up electrical signals through the scalp, with no operating theatre involved. The company […] This story continues at The Next Web
- 'Quality decays exponentially following AI arrival': Research shows experts and contributors leaving online communities amidst silent 'knowledge reset'
AI may have killed Stack Overflow while training on the same platform, as it pushed expert contributors away from the platform
- KAIST develops AI technology to detect early warning signs of cerebrovascular disease at home
KAIST develops AI technology to detect early warning signs of cerebrovascular disease at home EurekAlert!
- Apple sues OpenAI, two former employees
Over alleged trade secrets theft.
- Could AI help al-Qaeda and other groups plan terror attacks?
Followers of extremist groups regularly ask how AI can help them plan terrorist attacks. A new study suggests that about one-third of AI chatbots might help them, if asked the right way.
- S&P Global sees OpenAI as a "key credit risk" for Oracle and cuts its credit rating
S&P Global has downgraded Oracle's credit rating to "BBB-," one notch above junk status. OpenAI accounts for roughly half of Oracle's $638 billion in contractual obligations. If OpenAI walked away, Oracle would be stuck with massive data center capacity it couldn't fill. The article S&P Global sees OpenAI as a "key credit risk" for Oracle and cuts its credit rating appeared first on The Decoder .
Score: 83🌐 MovesJul 12, 2026https://the-decoder.com/sp-global-sees-openai-as-a-key-credit-risk-for-oracle-and-cuts-its-credit-rating/ - Meta kills Muse Image feature that let anyone generate AI photos of Instagram users without consent
Meta pulled a controversial feature from its new Muse Image model after widespread criticism. The feature let users generate AI images of other people by @-mentioning their public Instagram accounts. No consent needed, just a username. Meta admits "this feature missed the mark" and shut it down days after announcing it. The article Meta kills Muse Image feature that let anyone generate AI photos of Instagram users without consent appeared first on The Decoder .
- Apple’s M6, M7 and M8 Chips Show How AI Is Reshaping the Company
Also: New Apple Pencils are coming.
- India's Tata Consultancy Services plans up to 8,900 AI deployment engineers, seeks AI acquisitions
India's Tata Consultancy Services plans up to 8,900 AI deployment engineers, seeks AI acquisitions Reuters
- IT services giant TCS takes an AI-led avatar
TCS’ global delivery centre in Cincinnati serves as a hub for AI innovation
- Critics question federal prison agency’s AI plans for inmate assessments
Critics question federal prison agency’s AI plans for inmate assessments Toronto Star
- Scientists’ Side Hustle? Using AI and Quantum Computing to Generate New Peptides
Researchers cobbled together funding and time to show how quantum computing could aid in the development of drugs to help underserved populations and combat rare diseases.
Score: 80🌐 MovesJul 12, 2026https://www.wired.com/story/scientists-using-ai-and-quantum-computing-to-generate-new-peptides/ - TCS announces new Global Business Units amid AI-led transformation
TCS has carved out ‘Autonomous Business Operations’, a dedicated sales organisation focused on driving sales motions specific to such operations.
- Trinidad and Tobago signs deals for data centers, despite history of chronic water shortages
Trinidad and Tobago signs deals for data centers, despite history of chronic water shortages Fortune
- Israel Innovation Authority Invests Approx. NIS 70 Million in National Infrastructure for AI Models Based on Bio Data
Israel Innovation Authority Invests Approx. NIS 70 Million in National Infrastructure for AI Models Based on Bio Data azcentral.com and The Arizona Republic
- Unisound U2: The 266B Model That Scored 87.9% on PhD-Level Science for $0.15/M
On 7 June 2026, a Chinese speech-AI company that most people outside China have never heard of released a large language model that scored… Continue reading on Towards AI »
- TCS backs sovereign AI, opens talks with Indian model developers
Mythos access concerns ‘overblown’ because businesses have yet to unlock full potential of available AI models, says TCS CEO Krithivasan
- Meta spent a year being punished for its AI spending. Then it told investors how it would get the money back.
Meta has had a miserable year on the market, flat while the Nasdaq-100 climbed 18%. That changed abruptly, with the stock posting its best week since early 2024, CNBC reports. Shares rose about 6% on Friday and roughly 15% across the week. The move was not driven by advertising, the business that actually makes Meta’s money. […] This story continues at The Next Web
- Grades dropped from 96 to 48 percent when a Brown professor made students take the exam without AI
An economics professor at Brown University suspects most of his 86 students used AI to cheat on a take-home exam that averaged 96 percent. When he made the final an in-person test, 18 students dropped the course, nine didn't show up, and the average fell to 48.6 percent. Two large studies from China and UC Berkeley back up his case: where students lean on AI for homework, their proctored exam scores tank. The article Grades dropped from 96 to 48 percent when a Brown professor made students take the exam without AI appeared first on The Decoder .
- Every 48 Hours, a New Embodied AI Model Is Born: From BAAI World Model to Alibaba Qwen-Robot
June 2026 saw 13 new embodied AI models and world models released, tracking the shift from hardware benchmarks to software intelligence competition in embodied AI.
- Majority of U.S. workers support an AI wealth fund as tech layoffs surge, survey finds
A majority of U.S. employees now want an AI sovereign wealth fund to hold corporations more accountable, according to a recent survey, as tech layoffs rise.
Score: 76🌐 MovesJul 12, 2026https://www.cnbc.com/2026/07/12/majority-of-us-workers-support-ai-fund-amid-tech-layoffs-survey.html - The Sequence Radar #893: Last Week in AI: GPT-5.6, Grok 4.5, Muse Spark 1.1 and the Post-Chatbot Stack
Next Week in The Sequence:
- OpenAI CEO Altman is now "pretty sure" AI is net job-creating, which is quite the pivot from predicting mass layoffs
OpenAI CEO Sam Altman now says he's "pretty sure" AI has created more jobs than it's eliminated. That's a sharp turn from his earlier warnings about entire professions disappearing. Anthropic CEO Dario Amodei is walking back similar claims, too. But studies so far back neither the old doomsday predictions nor optimism. The article OpenAI CEO Altman is now "pretty sure" AI is net job-creating, which is quite the pivot from predicting mass layoffs appeared first on The Decoder .
- Memory giants race to expand AI chip capacity
Samsung Electronics, SK hynix and Micron Technology, the world's three largest memory chipmakers, are racing to expand production capacity as demand for artificial intelligence infrastructure continues to outpace supply. According to World Semiconductor Trade Statistics, the global semiconductor market is expected to grow 90 percent this year to $1.51 trillion. The memory market alone is forecast to surge 250 percent to $803.9 billion. The three rivals are accelerating investment in new fabricat
- Understanding the rise of agentic commerce
It promises convenience by reducing search costs and simplifying the consumer decision-making process
Score: 75🌐 MovesJul 12, 2026https://www.thehindubusinessline.com/opinion/understanding-the-rise-of-agentic-commerce/article71214165.ece - PHANES AI Writes Touch Into Robot Foundation Models: TouchWorld Tactile Model Enables Dexterous Manipulation
Founded by 28-year-old HIT professor Yang Shuo, PHANES AI publishes TouchWorld, a predictive and reactive tactile foundation model that gives robots a sense of touch to complete precise physical tasks.
Score: 75🤖 ModelsJul 12, 2026https://pandaily.com/phanes-ai-touchworld-tactile-foundation-model-jul2026 - Apple’s ‘Thermonuclear’ Response to the OpenAI Threat
Apple’s suit against OpenAI under Tim Cook echoes a familiar playbook, betting that litigation can delay a rival from upending the iPhone era.
Score: 75🌐 MovesJul 12, 2026https://www.wsj.com/tech/ai/apples-thermonuclear-response-to-the-openai-threat-8d51c814?mod=rss_Technology - Anthropic Illuminates LLM J-Space With J-Lens
Anthropic's J-space research reveals AI's hidden reasoning workspace without claiming the models possess consciousness or feelings.
Score: 74🤖 ModelsJul 12, 2026https://www.forbes.com/sites/johnwerner/2026/07/12/anthropic-illuminates-llm-j-space-with-j-lens/ - DeepSeek cut prices 75%. The 100x problem remains
DeepSeek's recent decision to drastically cut pricing on its V4-Pro model by 75% should have been unequivocally good news for enterprise AI vendors and developers. Instead, many are discovering that cheaper models don’t automatically translate into healthier margins. The reason is simple: While inference costs plummet, agent systems are voraciously consuming tokens faster than prices are declining. For the last 2 decades, software economics was dictated by the same rule. Infra became cheaper every year whereas applications became more capable. AI was initially hypothesized to follow the same pattern. As frontier models improved and token prices dropped, many assumed inference would become a negligible operating expense.That assumption has begun crumbling exponentially. A chatbot usually turns one user question into one model call. An agent turns it into a chain of planning, retrieval, tool use, verification, summarization, and follow-up decisions. The user sees one answer. The vendor pays for the loop. That is the 100x problem: The same user-visible request can cost a lot more to serve as an agentic workflow than as a chatbot or retrieval-augmented generation (RAG) response. In longer-running workflows, the multiplier is higher. Falling model prices help, but they do not fix a product architecture that turns one prompt into dozens of billable operations. The scale of what is now at stake is clear in how model providers themselves are pricing developer relationships. OpenAI's proposed program to give every Y Combinator startup $2 million in API credits — a number that would have funded an entire seed round in any prior tech cycle, and when the same cohort got by on a few thousand dollars of AWS credits — is less a recruiting perk than an admission of what it now costs to run an AI-native company through its first year of product. For established enterprises retrofitting agents into existing product lines, the absolute numbers are larger still. What token amplification is In a single-turn chatbot, one user message produces roughly one model call. Input-to-billed ratio is about 1:5. In a multi-step agent rolled out across customer support, sales operations, finance, legal review, and engineering, that ratio routinely lands at 1:700 or higher . Every loop iteration carries forward the cumulative conversation, tool outputs, and reasoning traces. Each step appends; nothing is dropped. A "simple" agent query like “ What did our top customer ask about last week?” typically touches seven priced operations before returning an answer: User prompt (~50 tokens) System prompt and tool definitions (~3,000 tokens, repeated on every call) Retrieval (~5,000 tokens of context) Model call #1 — tool selection (8,000 in / 200 out) Tool execution (~4,000 tokens returned) Model call #2 — summarization (12,000 in / 400 out) Model call #3 — follow-up decision (12,400 in / 100 out) One sentence in, roughly 35,000 input tokens billed. Somewhere between $0.10 and $0.40 per query on a frontier model. Multiply that by a million queries a month — the table-stakes volume for any enterprise B2B feature — and the line item is six figures. Why this breaks the existing AI business model The dominant pricing story for enterprise AI has been seat-based SaaS : Pay per-user per-month, deliver agent capability, capture margin. That model assumes a reasonably bounded cost-per-user. Token amplification breaks the assumption. A power user running 50 agent invocations a day on a $40/seat plan can cost more in inference than the plan charges. Token amplification shatters the traditional SaaS pricing model. When a power user’s daily agent activity costs more in inference than their monthly subscription fee, vendor gross margins turn negative, a paradox that compounds as customers deepen their agent adoption, the very usage curve vendors are selling to their boards. Several vendors are now privately reporting negative gross margins on heavy users, mirroring recent cloud expenditure reports from the Bessemer 'Supernova' cohort, where the correlation between AI-agent adoption and gross margin contraction has moved from a theoretical risk to a primary P&L headwind. The visible symptoms have started leaking into public coverage. Bloomberg this week documented a widening gap between Salesforce's Agentforce marketing demos and the capabilities actually shipping to customers. This is the kind of gap that opens predictably when promised functionality is technically possible but uneconomical to serve at the price the seat plan implies. Salesforce is the most-watched case, not a unique one. "For my team, the cost of compute is far beyond the costs of the employees." — Bryan Catanzaro, VP of Applied Deep Learning, Nvidia The strategic implication is not "AI is expensive." It is that the dominant business model assumed by most AI-native company plans does not survive contact with agentic workloads. A simple example Consider an enterprise software vendor charging $40 per-user per-month for an AI-enabled support assistant. A traditional chatbot might cost only a few cents per user per day in inference, leaving healthy gross margins. Now replace that chatbot with a fully agentic workflow capable of investigating tickets, querying internal systems, drafting responses, validating outputs, and escalating exceptions. If a heavy user executes 50 to 100 agent requests per day, inference consumption can increase by an order of magnitude. What was once a negligible infrastructure cost becomes a material operating expense. This creates an unusual dynamic: The customers receiving the most value from the product are often the customers generating the highest inference costs. In extreme cases, vendors can find themselves with their most engaged users contributing the least profit. The result is a growing realization across enterprise software that agent adoption and margin expansion are no longer automatically aligned. Agent orchestration is the new moat The technical responses are known and converging. They are not novel, but they are critical for survival Cost-aware routing : This technique involves a small classifier model that decides which tier (Haiku, Sonnet, Opus equivalents) handles each query. Well-tuned routers cut inference bills by around 60% without any degradation in quality Prompt caching : Anthropic , OpenAI, and Google now offer 75 to 90% discounts on cached prefixes. Context discipline : You can truncate tool outputs, prune reasoning traces, and cap tool depth to prevent your agent from going down a rabbit hole Speculative decoding : for self-hosted deployments, this technique guarantees 2 to 3X effective throughput on the same GPUs. "Organizations using orchestration-led governance report stronger productivity gains — a holistic orchestration layer is associated with six times greater productivity impact than compliance‑only approaches" — IBM The companies building this layer well are starting to look less like microservice operators and more like financial trading systems : Every routing decision priced, every path with its own P&L, every tenant on a metered budget. What enterprise leaders should actually do F our moves separate the companies that will still have margin in 24 months from the ones that won't: Make inference cost a first-class metric. Track it per-feature, per-tenant, per-query class the same way cloud cost was tracked starting in the mid-2010s. Budget like a media buyer. Set cost-per-thousand-queries ceilings per feature. Cap them. Alert on overruns. Engineering will not enforce this on its own. Treat the router as core infrastructure, not an optimization. It is the new load balancer. Audit prompts quarterly. A 4,000-token system prompt that grew organically over six months is a six-figure bill in slow motion. Most teams have never read their own production prompts end to end. Negotiate volume commits early. Frontier-model vendors now offer reserved-instance-style prepaid commits at substantial discounts. List price is the worst price any enterprise will ever pay. The next 24 months The structural shift underneath agentic AI is not that it is expensive. As DeepSeek's price cut today underscores, frontier inference unit costs are dropping roughly 3X per year, and the curve is not slowing. The shift is that amplification is outrunning the price cuts . Cutting per-token costs 75% does not help a company whose agents are doing 700X more tokens per user query than its pricing model assumed. For the first time since the cloud era began, architecture decisions are again financial decisions in real time. A prompt redesign is a margin event. A poorly bound agent loop is an outage with a credit card attached. The companies that survive the next 24 months of AI infrastructure pricing will not be the ones running the cheapest model. They will be the ones whose agents are smart and know what they cost to think. That is the 100X problem. And it is arriving faster than the price cuts can hide it. Maitreyi Chatterjee is a senior software engineer at a big tech company. Devansh Agarwal works as an ML engineer at a leading tech company.
Score: 74🌐 MovesJul 12, 2026https://venturebeat.com/orchestration/deepseek-cut-prices-75-the-100x-problem-remains - Dexmal Aims to Ignite Embodied AI Productivity With DM0.5 Model, DexOS, and MaaS Three-Stage Strategy
Dexmal releases DM0.5 foundation model, Apex universal robot, DexOS operating system, and MaaS platform, targeting the final engineering gap between embodied AI models and real-world productivity.
- Can AI Make Better Drugs? Not on Wall Street’s Timeline
The technology has arrived in the drug lab. But should investors pay up for it?
Score: 73🌐 MovesJul 12, 2026https://www.wsj.com/tech/ai/can-ai-make-better-drugs-not-on-wall-streets-timeline-98a50d9d?mod=rss_Technology - Zhipu’s Chinese Founder Says Frontier AI Should Stay Open to All
The founder of Chinese AI lab Zhipu argued that frontier artificial intelligence should remain broadly accessible rather than controlled by select individuals, weighing in on a growing debate about the risks posed by ever more powerful models.
- Grok Linked to Sickening Crime in Lawsuit That Puts SpaceX in Crosshairs
And its developers "remained silent." The post Grok Linked to Sickening Crime in Lawsuit That Puts SpaceX in Crosshairs appeared first on Futurism .
Score: 72🌐 MovesJul 12, 2026https://futurism.com/artificial-intelligence/grok-linked-sickening-crime - Apple’s failed self-driving car program left a legacy of powerful AI chips
Apple's self-driving car program never really got off the ground, but it may have been what made the company's chips the powerful AI performers they are. Early in the development of the self-driving platform, Apple realized that it would need powerful on-device AI processing. While the car processor was never finished, as Mark Gurman details […]
Score: 71🌐 MovesJul 12, 2026https://www.theverge.com/tech/964519/apple-silicon-self-driving-car-ai-m7-ultra - Children's brand caught using photo without permission, turning Asian boy into white child with AI
Susu & Cra, a South Korean children's clothing brand, apologized for using a photograph owned by the smaller Korean bedding company Boni Moire without permission and modifying it with AI. The issue arose on Friday when Boni Moire accused Susu & Cra in a Threads post of using a photograph of a sleeping young boy without permission and modifying it for promotional material. "It looks like my son's photo," the post said. "I think they changed the boy's hair color, hand, and blanket. I posted the or
- Is India drinking itself dry for AI economy?
India’s challenge is not whether to build for the AI economy, but whether it can do so without exhausting the very resources that sustain growth
Score: 71🌐 MovesJul 12, 2026https://www.thehindubusinessline.com/opinion/is-india-drinking-itself-dry-for-ai-economy/article71206654.ece - Govt eyes Nvidia investment to increase data center capacity
By the senior economy minister's estimates, the project could cost up to $720 million in total to expand capacity from 580 MW at present to the targeted 1.3 GW at around $1 million per MW, though he did not say how much of that might be footed by the American chip-making giant.
- Most Americans now say the public should own half of the big AI companies
An idea that sounded radical a year ago is now a majority position. Nearly seven in ten Americans support forcing AI companies to transfer half their stock to a public sovereign wealth fund, CNBC reports. The figure comes from a Verasight survey of 1,690 US adults, conducted in June. It found 69% backing for the policy. […] This story continues at The Next Web
Score: 70🌐 MovesJul 12, 2026https://thenextweb.com/news/most-americans-now-say-the-public-should-own-half-of-the-big-ai-companies - OpenAI, Meta, SpaceXAI Compete for More Cost-Efficient AI Models
Three prominent artificial intelligence developers released new models over the past week. They all promise to be more advanced, but their biggest immediate selling point may not be what they can do but how little they charge to do it.
- TechCrunch Mobility: A robotaxi ultimatum
Welcome back to TechCrunch Mobility, your hub for the future of transportation and now, more than ever, how AI is playing a part.
Score: 70🌐 MovesJul 12, 2026https://techcrunch.com/2026/07/12/techcrunch-mobility-a-robotaxi-ultimatum/ - Uber’s Autonomous Vehicle Strategy: Slow Their Adoption
In at least two places, Uber has pushed a policy that could give it an advantage over developers of self-driving cars. The company says it’s fighting monopolies.
Score: 69🌐 MovesJul 12, 2026https://www.wired.com/story/ubers-autonomous-vehicle-strategy-slow-their-adoption/ - The AI race has quietly stopped being about who has the biggest model
For years the industry ran on one assumption, that the biggest model wins. That belief is now breaking down, CNBC reports. Companies are choosing models by task, cost, and control instead of benchmark position. The frontier still matters, but it is no longer the only thing being bought. The reason is unromantic. At enterprise scale, model […] This story continues at The Next Web
Score: 69🌐 MovesJul 12, 2026https://thenextweb.com/news/ai-race-shifts-bigger-models-to-cheaper-systems - Grok 4.5 Uses 4.2x Fewer Tokens and Costs 17x Less Than Opus 4.8
Grok 4.5 is the fourth-smartest model in the world, and that is not the interesting number. On Artificial Analysis’s independent… Continue reading on Towards AI »