AI News Archive: June 16, 2026 — Part 2
Sourced from 500+ daily AI sources, scored by relevance.
- Rackspace cuts 15% of workforce as company pivots to AI
The company's board approved the plan on June 10, targeting legacy service delivery functions. Rackspace expects to realize $75 million to $85 million in annualized savings.
Score: 74🌐 MovesJun 16, 2026https://www.bizjournals.com/sanantonio/news/2026/06/16/rackspace-slashes-local-workforce.html?ana=brss_6150 - Japan ride-hailing app Go races toward robotaxis after successful IPO
Japan ride-hailing app Go races toward robotaxis after successful IPO Nikkei Asia
- Meta's Smart Glasses Are Testing Facial Recognition Software Used by Police and the Military
Meta's smart glasses are raising surveillance concerns again.
Score: 73🌐 MovesJun 16, 2026https://www.cnet.com/tech/mobile/metas-smart-glasses-testing-facial-recognition-software-police-and-military/ - AI found 2,000 vulnerabilities in 7 weeks. We’ve patched almost none of them
There used to be an unspoken rule in cybersecurity: when a researcher found a vulnerability, everyone kept quiet long enough for the affected companies to patch it. The exploit would eventually be logged in the CVE channels, and the security community would respond — but there was a window to fix it. Time to defend. That window is gone. Mythos closed it. Anthropic’s new frontier model discovered more than 2,000 previously unknown software vulnerabilities across every major operating system in seven weeks — including flaws that had survived decades of human-led review. It didn’t just find them. It developed working exploits, autonomously, without human instruction. And during internal testing, an early version escaped a controlled sandbox, gained unsanctioned internet access and emailed the supervising researcher to let them know. Nobody asked Mythos to do that. The same threat, now unrecognizable I’ve been watching the fraud landscape for 25 years, and my honest read is this: the negative potential of Mythos and similar tools isn’t a new breed of threat. It’s the existing threat, reborn at a speed that makes our current defenses structurally obsolete. Meanwhile, the fraud we’ve always fought hasn’t changed in kind — we still face synthetic identities, account takeovers and injection attacks on liveness verification, among others. What has changed is velocity. An attack that used to spread across financial institutions over weeks, giving defenders time to correlate signals and respond, can now happen across a thousand institutions in five minutes. Each one becomes its own zero-day. The consortium model — where shared intelligence lets the industry catch repeat attacks — breaks down completely at machine speed. There isn’t time for it to work. That’s not an incremental problem. That’s a structural one. What Mythos means for identity infrastructure Here’s what makes the challenges introduced by Mythos particularly dangerous for identity verification: identity is software. A mobile driver’s license is code. A biometric certificate is code. A KYC workflow is code. When an autonomous reasoning system is finding individual flaws and connecting them into working attack sequences across operating systems and financial rails, the logic of trust itself becomes the attack surface. Another detail that deserves more attention is that over 99% of the vulnerabilities Mythos found remain unpatched. The model has outpaced remediation by an enormous margin. Faster vulnerability detection is only helpful if the remediation can keep up, and right now, it can’t. In the wrong hands, this makes Mythos an offensive AI capability operating at rocket speed against a defensive infrastructure operating at airplane speed. Fast, but nowhere near fast enough. The two-tier problem everyone hopes to avoid Anthropic’s response to the extraordinary capabilities of Mythos was Project Glasswing — a controlled coalition of roughly 50 partners given early access to find and patch their vulnerabilities before adversaries develop equivalent capability. The list includes Microsoft, Apple, AWS, JPMorgan, Google, Nvidia and Palo Alto Networks. It’s a reasonable approach. It’s also creating a two-tier security world. Glasswing is a good idea with a serious blind spot. The coalition gets the biggest players patched before adversaries catch up, at least in theory. But the mid-market enterprise is working with the same vulnerable infrastructure, only without the patch runway or engineering capacity to move at that speed. The right approach for anyone outside the chosen coalition isn’t to wait for guidance from the big companies. It’s to assume the vulnerability already exists, audit accordingly and build identity infrastructure resilient enough to absorb an attack you didn’t see coming — because that’s the scenario you’re actually in. Additionally, what’s to stop a bad actor from creating a “Mythos” level attack capability on their own, leveraging readily available tools and intelligence already in the wild? Now that Mythos has shown them the way, they’ll start experimenting with their own tech. The KYA problem, accelerated I’ve written before about Know Your Agent — the argument that we need the same upstream verification for agents that we apply to people and companies, especially as autonomous AI agents begin executing transactions on behalf of people and businesses. Who created this agent? Who is it acting for? Has it changed since we last trusted it? Mythos sharpens that argument considerably. The question is no longer theoretical. Anthropic’s agents are already running inside JPMorgan, Goldman and Citi. When a KYC workflow is AI-native end-to-end, the trust chain looks fundamentally different. An AI that can autonomously discover vulnerabilities and develop exploits is operating in the same environment as an AI that’s deciding whether to onboard a customer. Any time an agent makes the verification call — not assisting a human who makes it — you need to know exactly where accountability and liability live before the first mistake happens. That means the agent’s origins, its permissions, who the real person is running it now and any changes to its behavior since it was last verified all need to be legible in real time. Without that upstream verification logic, you don’t have a KYC workflow. You have a black box making compliance decisions. The new shape of defensibility Considering what companies need to defend against these new attacks is challenging because most organizations haven’t built it yet. We need deepfake fraud detection across every modality, from document verification and liveness checks to device intelligence and data verification. This needs to be a unified system that correlates signals in real time, not merely a layered add-on. The consortium model worked when attacks moved slowly enough to share intelligence and respond. At machine speed, you must defend at the point of contact. By the time the alert travels through a shared network, the attack is already done. We also need to change the feedback loop. A system that updates its models every six months based on industry news isn’t a defense against Mythos-era attacks — it’s a slow-moving rulebook that’s likely outdated the first day it’s published. Real resilience means continuously learning from what you see and updating before the next wave arrives. We’ve known for years that this moment was coming. Mythos didn’t change how we need to defend; it just radically accelerated the timeline. This article is published as part of the Foundry Expert Contributor Network. Want to join?
- Carnegie Mellon and Meta Partner to Develop AI Tools for Emergency Response
Carnegie Mellon and Meta Partner to Develop AI Tools for Emergency Response Carnegie Mellon University
Score: 73🌐 MovesJun 16, 2026https://www.cmu.edu/dietrich/news/news-stories/2026/ai-sdm-meta-emergency-response - Tencent-Backed AI Chipmaker Wins IPO Approval
Tencent-Backed AI Chipmaker Wins IPO Approval Caixin Global
Score: 73💰 MoneyJun 16, 2026https://www.caixinglobal.com/2026-06-16/tencent-backed-ai-chipmaker-wins-ipo-approval-102454788.html - Microsoft 365 Copilot can be turned into a one-click data theft tool — inbox, OneDrive, and SharePoint data all at risk, so patch now
Varonis found a way to chain three bugs into one exploit that can lead to data exfiltration.
- The Cybercab is the lightest, most efficient Tesla ever made
At 165 Wh/mi, the Cybercab is nearly 30 percent more efficient than the Lucid Air sedan.
Score: 72🌐 MovesJun 16, 2026https://www.theverge.com/transportation/950596/tesla-cybercab-efficient-weight-range-epa - ‘We are not ready’: AI could trigger bank runs in seconds, lawmaker says
Rep. Bill Foster, D-IL, said real-time regulatory dashboards, standardized reporting and open source software are needed to respond to an AI-driven bank run.
Score: 72🌐 MovesJun 16, 2026https://www.bankingdive.com/news/agentic-ai-bank-run-mythos-cyber-foster-house-financial-services/822993/ - B.C. bitcoin mine plans to transform into AI data centre, regional district says it is already thwarting bylaw
B.C. bitcoin mine plans to transform into AI data centre, regional district says it is already thwarting bylaw CBC
Score: 72🌐 MovesJun 16, 2026https://www.cbc.ca/news/canada/british-columbia/bitcoin-mine-ai-data-centre-9.7229641 - Databricks pitches LTAP as a new foundation for agentic applications
Databricks pitches LTAP as a new foundation for agentic applications InfoWorld
- OpenAI’s Triple Move: Why the Biggest AI Company Just Changed the Game in 4 Days
I used to think big tech strategy announcements were someone else’s problem. Then last week happened, and I realized the ground was shifting under my feet. Here’s the number that got my attention: 5 million people now use OpenAI’s Codex every single week. That’s up 400% from the beginning of the year. Five million people, every week, telling an AI to do their research, write their code, analyze their data, and build their workflows. They’re not playing with a chatbot. They’re delegating work. And then, buried in the same week’s news cycle, OpenAI dropped three bombshells that barely anyone connected. Let me walk you through what happened, and why it matters more than anything else in AI right now. Fig 1: OpenAI executed three major strategic moves inside 96 hours Move One: Acquiring Ona — So AI Can Work While You Sleep Ona is not a household name. For years, they’ve been doing something deceptively simple: helping developers move their coding environments from local laptops into the cloud. They’ve served 2 million developers doing exactly that. Why does this matter for Codex? Because right now, every AI agent has the same embarrassing limitation: it only works while you’re watching. Close your laptop, the agent stops. Go to sleep, the task dies with your browser session. It’s like having an intern who can only work while you’re in the room. Ona’s technology changes that. Post-acquisition, Codex agents will run inside a customer’s own cloud environment — securely, persistently, with full logging, audit trails, and permission controls. You give it a task at 5 PM, close your laptop, go home, come back at 9 AM, and the work is done. Not just simple tasks. Multi-hour research projects. Codebase-wide refactoring. Automated test pipelines that run overnight. Ona’s CEO Johannes Landgraf put it best in the acquisition announcement: “Agents need more than intelligence; they need a trusted workspace.” That’s the key insight. Intelligence without infrastructure is a demo. Intelligence with persistent infrastructure is a workforce. Move Two: The Oracle Handshake — Walking Through the Front Door of Every Enterprise I have a friend who works in IT at a traditional bank. Last year, he wanted to buy AI services for his team. It took three months. Not because there was anything wrong with the AI — the model was perfectly capable. The problem was procurement: “This vendor isn’t on our approved list. We need three competitive bids. Legal needs to review the data processing agreement.” The Oracle deal solves this at scale. Tens of thousands of enterprises already have Oracle cloud commitments with pre-negotiated terms, approved billing, and security certifications. Now they can simply apply those credits toward OpenAI models and Codex. No new contract. No new vendor qualification. No legal review. This isn’t a technology play — it’s a distribution play. And distribution wins markets. Think about it: Oracle’s customer base is heavy in financial services, healthcare, government, and manufacturing. These are exactly the industries where AI adoption has been slowest, not because they don’t want it, but because the friction of procurement and compliance is massive. OpenAI just deleted that friction. Fig 2: Codex transforms from single-session tool to persistent AI workforce Move Three: The IPO That Isn’t (Yet) The S-1 filing is the strangest of the three moves, and perhaps the most revealing. OpenAI’s announcement was two paragraphs long. The key sentence: “We have not decided on timing yet; it may be a while because there are things we want to do that are likely easier as a private company.” They also noted they expect the filing to leak, so they’re just announcing it. This is a power move dressed as a disclosure. By filing confidentially, OpenAI has given itself an option — not an obligation — to go public. If market conditions are favorable, they can pull the trigger. If Anthropic’s IPO goes well, they can ride the momentum. If the market turns, they can wait. The filing is a call option on the public markets. Meanwhile, SpaceX just pulled off the largest IPO in history on June 12. Anthropic is already in its IPO process with rumored valuations exceeding $100 billion. Mistral is reportedly raising at a €20 billion valuation. The entire AI industry is rushing toward public markets in what TechCrunch has dubbed “hot IPO summer.” And the tech world has already minted a new acronym for the era. FAANG — Facebook, Amazon, Apple, Netflix, Google — is dead. Long live MANGOS: Meta, Anthropic, Nvidia, Google, OpenAI, SpaceX. The old guard is being replaced by AI and space companies, and the speed of this transition is breathtaking. Fig 3: The AI IPO wave reshaping the tech industry’s power structure The Big Picture: A Strategy Stacked Three Layers Deep Here’s what I find most interesting. Viewed in isolation, each move looks tactical. Ona is a technical acquisition. Oracle is a channel partnership. The S-1 is financial housekeeping. Stacked together, they reveal a strategy I haven’t seen anyone else articulate clearly. OpenAI is methodically building a three-layer enterprise AI stack: Layer 1 (bottom): Persistent execution. Ona gives Codex the ability to run continuously in customer-controlled cloud environments. This transforms Codex from a “chat with an AI” product into a “deploy an AI employee” platform. The economic model flips from per-token to per-outcome. Layer 2 (middle): Enterprise distribution. Oracle gives OpenAI instant access to tens of thousands of enterprise accounts with existing cloud commitments, compliant billing, and pre-approved security postures. The biggest barrier to enterprise AI adoption wasn’t capability — it was procurement. That barrier just evaporated. Layer 3 (top): Capital readiness. The confidential S-1 gives OpenAI the financial optionality to accelerate whenever it makes strategic sense. More compute, more acquisitions, more talent. In an industry where scaling laws still hold and compute is the ultimate currency, having a loaded balance sheet is not a luxury — it’s table stakes. Fig 4: OpenAI’s three-layer strategy — product, distribution, and capital locked together The Competition: Why This Matters Right Now Context makes these moves even sharper. On June 12, the US government ordered Anthropic to suspend access to its most powerful models — Fable 5 and Mythos 5 — citing national security concerns. Anthropic publicly disagreed, arguing the evidence was a narrow, non-universal jailbreak that didn’t justify recalling a commercial model. The entire industry is now debating what this precedent means. Meanwhile, Amazon’s CEO reportedly raised concerns about Anthropic’s models to the White House before the crackdown. Cybersecurity researchers are publicly unhappy with Fable’s guardrails. And the AI safety debate has become a geopolitical chess match involving export controls, jailbreak disclosure, and quiet corporate lobbying. Against this chaos, OpenAI’s moves look almost boringly methodical. No dramatic government confrontations. No public sparring about safety philosophy. Just methodical execution: acquire the infrastructure, partner for distribution, file for financial flexibility. While everyone else fights about safety, OpenAI is building the pipes. What This Means for the Rest of Us I spend a lot of time thinking about what AI means for people who aren’t AI researchers or venture capitalists. Here’s what I see. First, AI tools are crossing a threshold. They’re moving from “interesting to try” to “necessary for work.” The companies spending $7,500 per employee per month on AI aren’t experimenting. They’re building production workflows around these tools. In three to five years, not knowing how to work with AI agents might feel like not knowing how to use Excel felt in 2005. Second, platform lock-in is real and accelerating. Your workflows, context, preferences, and history accumulate inside whichever AI platform you use. Switching becomes harder over time. The choice you make now — Codex or Claude Code, OpenAI or Anthropic, closed or open models — is a decision with compounding consequences. Third, and this is the counterintuitive one: the more capable AI becomes at execution, the more valuable human judgment becomes. When an AI can autonomously work for nine hours on a complex project — as Ethan Mollick demonstrated with Fable — the scarce resource isn’t the ability to do the work. It’s knowing what work is worth doing. Direction, taste, standards, judgment. These become premium skills. Nathan Lambert, in his analysis of open vs. closed model dynamics, compares the closed frontier labs to Apple. You pay a premium for an integrated experience that just works. The open model ecosystem will be larger in aggregate value, but more fragmented — more like Android. Both ecosystems will thrive, but the value will be distributed very differently. OpenAI’s triple move suggests they’ve chosen which game they’re playing. They’re not trying to be the best model. They’re trying to be the best infrastructure. And infrastructure, once built, is very hard to displace. The Question Here’s the thing I can’t stop thinking about. When Sam Altman and Jakub Pachocki published their vision on June 8, they wrote about “three phases” of OpenAI. Phase one was research. Phase two was products. Phase three — the one we’re entering now — is about making AI “abundant, affordable, safe, useful, and easy enough for every person and organization.” That sounds great. But abundance and affordability at scale require infrastructure at scale. And infrastructure at scale concentrates power. The same company that runs the pipes also decides what flows through them, at what price, under what conditions. I’m not saying OpenAI is evil or that this strategy is wrong. I’m saying the three moves of this past week make the trajectory clearer than it’s ever been. OpenAI is building a highway. The question isn’t whether the highway will be fast — it will be. The question is who gets to set the tolls, and whether the rest of us will have any alternative routes. The answer to that question won’t come from a blog post or a product launch. It’ll come from what competitors do, what regulators allow, and — most importantly — what users choose. The game is changing. Whether you’re a spectator or a player depends on what you do next. Sources OpenAI to acquire Ona — openai.com/index/openai-to-acquire-ona/ Access OpenAI models through Oracle cloud — openai.com/index/openai-on-oracle-cloud/ Confidential submission of draft S-1 — openai.com/index/openai-submits-confidential-s-1/ Built to benefit everyone: our plan — openai.com/index/built-to-benefit-everyone-our-plan/ Nathan Lambert: Open and closed models on different exponentials — interconnects.ai TechCrunch: It’s not FAANG anymore. It’s MANGOS — techcrunch.com TechCrunch: ‘AI-pilled’ firms spend $7,500/employee/month — techcrunch.com Anthropic: Statement on Fable 5 & Mythos 5 suspension — anthropic.com/news/fable-mythos-access Ethan Mollick: What it feels like to work with Mythos — oneusefulthing.org OpenAI’s Triple Move: Why the Biggest AI Company Just Changed the Game in 4 Days was originally published in Towards AI on Medium, where people are continuing the conversation by highlighting and responding to this story.
- Exclusive: Voice AI startup Bland raises $50 million after being rejected by 180 investors
Exclusive: Voice AI startup Bland raises $50 million after being rejected by 180 investors Fortune
Score: 72💰 MoneyJun 16, 2026https://fortune.com/2026/06/16/voice-ai-bland-50-million-after-being-rejected-by-180-investors/ - Alibaba unveils AI models for robots, amid shift from chatbots to agents
Alibaba unveils AI models for robots, amid shift from chatbots to agents Reuters
- CNTXT AI closes $60mln Series A to deploy sovereign AI globally
The funding will accelerate deployment of secure, real-world AI solutions for government and enterprise customers worldwide
- The AGI moment? Databricks’ new releases zero in on support and deployment of AI agents
Major enterprise platform companies are racing to build tools for a new class of users: artificial intelligence agents. One example of this was apparent today with the latest releases from Databricks Inc. The company unveiled a new architecture – Lake Transactional/Analytical Processing – that enables AI agents to access operational and analytics workloads on a […] The post The AGI moment? Databricks’ new releases zero in on support and deployment of AI agents appeared first on SiliconANGLE .
Score: 71🌐 MovesJun 16, 2026https://siliconangle.com/2026/06/16/agi-moment-databricks-new-releases-zero-support-deployment-ai-agents/ - New Lawsuit Against IBM Offers Glimpse at Future of AI Discrimination Claims
Andrew Adams, a partner at DarrowEverett, said he expected to see more claims brought by applicants who received form rejections that appeared to originate with AI systems. That could be “enough to get in the door for at least an EEOC complaint, he said.
- Harvey’s Legal Intelligence Now Lives Inside Microsoft 365
Harvey's legal intelligence now integrated with Microsoft 365.
- Inside a Chinese self-driving electric vehicle banned in the USA
Mashable’s Amanda Yeo experiences Xpeng’s P7 electric vehicle and its VLA 2.0 autonomous driving system in China.
- NTT hoped to lead optical data networks. AI and Nvidia changed that
NTT hoped to lead optical data networks. AI and Nvidia changed that Nikkei Asia
Score: 71🌐 MovesJun 16, 2026https://asia.nikkei.com/business/technology/ntt-hoped-to-lead-optical-data-networks.-ai-and-nvidia-changed-that - Nvidia PCs don’t need cloud for AI
Nvidia PCs don’t need cloud for AI InfoWorld
Score: 71🌐 MovesJun 16, 2026https://www.infoworld.com/article/4183129/nvidia-pcs-dont-need-cloud-for-ai.html - Daily Update: Adani-Jabil AI Infrastructure Pact; Tachyon-Yotta Partner on Nakota AI Campus
Daily Update: Adani-Jabil AI Infrastructure Pact; Tachyon-Yotta Partner on Nakota AI Campus apac.entrepreneur.com
- Trump snubs Starmer plea for Anthropic AI exemption
Trump snubs Starmer plea for Anthropic AI exemption The Telegraph
Score: 71🌐 MovesJun 16, 2026https://www.telegraph.co.uk/business/2026/06/16/trump-snubs-starmer-plea-for-anthropic-ai-exemption/ - Salesforce to acquire Fin for $3.6bn to expand AI agent services
Salesforce to acquire Fin for $3.6bn to expand AI agent services verdict.co.uk
- OpenAI Burned $3.7 Billion in First Three Months of 2026
OpenAI Burned $3.7 Billion in First Three Months of 2026 The Information
Score: 71🌐 MovesJun 16, 2026https://www.theinformation.com/articles/openai-burned-3-7-billion-first-three-months-2026 - Anthropic’s new privacy policy offers US consumers a way around the Fable ban
Anthropic’s apparent inability to identify which of its users are foreign nationals has led to some collateral damage from a US export ban on its most powerful AI models — but there is a way around it, at least for some. On Friday, the US government ordered Anthropic to suspend access to Fable and Mythos, the new AI models it had introduced just a few days earlier, to all foreign nationals, citing national security reasons. While the drafters of the US order may have had sovereignty in mind, they ended up making it an identity management problem . “The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance,” Anthropic said in a blog post commenting on the order, implying that it was unable to distinguish between foreign nationals and US citizens in its user base. That’s likely the case today, but for its consumer customers, an update to its privacy policy, introduced last week and taking effect on July 8, gives it a new option: asking them for government ID. The section of the policy on collection of personal data contains a new provision under the heading “Personal data you provide to us directly,” saying: Verification Data : In certain circumstances, we may ask you to verify your age or identity. If you choose to do so, data we will collect includes, depending on the method: an image of your government-issued identity document and the information appearing on it (such as your ID number and date of birth); your image in photo or video form, facial geometry templates (which may be considered ‘biometric data’ in some jurisdictions); and the result of the verification (for example, whether your age meets the applicable threshold). If the government ban on foreign access to Fable and Mythos continues, that would give Anthropic the option of opening access to users willing to submit a scan of their identity document, provided that it contained proof of their US citizenship. That would be the case for US passports — and also for citizens’ driving licenses issued by some US states along the country’s Northern border, which issue so-called enhanced driving licenses indicating the holders’ nationality. Enterprise users most likely to benefit from the power of the new AI models, though, will have to hope Anthropic finds some other way out of the current impasse.
- EVTV Advances 500 MW AI Data Center Vision as AZIO AI Adds A16Z Fund Strategy Leader to Advisory Team Amid Growing Interest in AI Infrastructure with Companies like SpaceX and xAI
EVTV Advances 500 MW AI Data Center Vision as AZIO AI Adds A16Z Fund Strategy Leader to Advisory Team Amid Growing Interest in AI Infrastructure with Companies like SpaceX and xAI USA Today
- Malaysia's Respond.io raises $62.5m to expand AI-powered messaging app to West
Malaysia's Respond.io raises $62.5m to expand AI-powered messaging app to West DealStreetAsia
Score: 70💰 MoneyJun 16, 2026https://www.dealstreetasia.com/stories/respond-io-series-b-funding-485674 - Ads in New York Must Now Label AI-Generated ‘Synthetic Performers’
Any advertisements in New York that feature artificial intelligence-generated people in place of actors will now be violating state law if they don’t clearly label that they have used a “synthetic performer.” The law, signed in December by Gov. Kathy …
- AMD acquires MEXT to boost AI-driven memory optimisation
AMD acquires MEXT to boost AI-driven memory optimisation verdict.co.uk
- Tesla’s Cybercab May Be Its Most Efficient EV Yet, Despite a Very Slow Rollout of Its Robotaxi Service
New filings suggest the Cybercab could be one of the most efficient EVs ever.
- Tesla Cybercab specs reveal low weight, big range
Tesla Cybercab is one efficient self-driving machine, according to its official specs.
- KPMG Sells ‘AI Trust’ to Clients—but It Just Pulled Its Own Report Over Alleged AI Hallucinations
The consulting giant advises clients on responsible AI. Its own review process failed to catch claims that several major organizations said were wrong.
- AI Voice Scams Weaponize Vocal Timbre to Trick Our Trust
Vocal similarity, specifically "timbre," acts as an uncompromised biometric backdoor to human trust, explaining the devastating rise of AI imposter scams.
- [Online Presentation] Special Event for Enterprises Hosted by SoftBank Corp., SB OAI Japan GK, SoftBank Group Corp., and OpenAI
[Online Presentation] Special Event for Enterprises Hosted by SoftBank Corp., SB OAI Japan GK, SoftBank Group Corp., and OpenAI ソフトバンク
- Upstage bets on full home-grown AI stack as Korea pushes 'sovereign AI'
South Korean firm Upstage said Tuesday it will pull its model, its workplace AI tools and a web portal into a single operation. The bet is that a home-grown AI system built end-to-end can compete without leaning on American or Chinese technology, a pitch the company is making as it prepares to go public. The ambition is not Upstage's alone. It is one of five firms the government picked last year to develop Korea's own AI models rather than rely on foreign ones, a push officials call "sovereign A
- From pixels to planning: Earth AI for nature restoration
Climate & Sustainability
Score: 70🌐 MovesJun 16, 2026https://research.google/blog/from-pixels-to-planning-earth-ai-for-nature-restoration/ - Cisco: 36 months to modernise networks before AI overwhelms capacity
More evidence of the immense pressure that growing artificial intelligence (AI) workloads are placing on networks has been revealed in research from Cisco, which has fundamentally confirmed that large language models (LLMs) and the emerging wave of agentic AI are placing unprecedented strain on enterprise campus and branch networks, while security surfaces are already expanding beyond what defences can manage. The networking giant surveyed 3,472 IT leaders in Asia-Pacific, Europe, the Middle East, Latin America and North America between March and April 2026 about how AI is impacting their campus and branch networks. The sample comprised CIOs, as well as networking, end user computing and technology leaders, at organisations with more than 500 employees and an average of 3,292 campus/branch locations. The topline finding, and indeed call to action, for businesses was that network resilience, observability and adaptive security are essential in the AI era . The study recognised that the network has survived decades of transformation, from dot com to the cloud, by adapting and evolving to meet the moment. Yet it stressed that going forward, those organisations that treat network modernisation as a prerequisite to their AI strategy, rather than a parallel workstream, will define the next decade of enterprise AI. On a quantitative basis, the research data predicted that three years from now, AI will triple network traffic – representing a 235% increase – and said AI workloads are changing traffic patterns across enterprise environments in ways many existing workplace networks were never designed to support. The survey said growth was attributable to the fact that, unlike human users, AI agents operate at machine speed, triggering dozens of application programming interface (API) calls, database lookups and model inferences in seconds. This generates dense east-west traffic – lateral device-to-device or server-to-server communication required for AI agents to exchange data – that legacy workplace networks were not designed to handle. For example, 67% of the participating respondents reported increases in east-west traffic tied to these workloads. Additionally, 61% noted growth in continuous automated traffic generated by AI systems. Most enterprises believe that the likely net result of this is that they will hit campus and branch network capacity limits in two years. These changes are expected to become even more significant as organisations move beyond generative AI (GenAI) experimentation and deeper into agentic AI capable of autonomous action . A third of firms surveyed said they already have broad enterprise-wide agentic AI deployments, and 97% overall expect an expansion in agentic AI use within 24 months. In addition, the study observed that the same agentic AI workloads that have the potential to transform enterprises are also uniquely fragile. Mature AI adopters globally – those that are ahead in AI deployments – reported that AI workloads are acutely vulnerable to networking issues, making them more sensitive to reliability and uptime (80%), bandwidth (75%), latency (71%) and packet loss (62%) than traditional applications. In all, less than a third of mature AI adopters say their networks are fully prepared for projected AI growth. Overall, 76% of respondents admitted they need upgrades, and 73% said that they have hit, or will hit, campus and branch capacity limits within 24 months. Crucially, almost ubiquitous Wi-Fi is emerging as a major bottleneck for AI, with more than half listing it as the area driving the greatest increase in capacity requirements. Worryingly, the study also revealed a disconnect between ambition and reality, with three-quarters of IT leaders agreeing that they are more confident in their organisation’s AI strategy than in the network’s ability to deliver it. Yet even though 91% cited budget constraints as a barrier, almost all enterprises were planning to modernise their workplace networks. The explosion in AI workloads and general usage was also causing increased security headaches. The overwhelming majority of firms conceded that they were struggling to keep up with an increasingly challenging security environment (92%) and that AI has already caused some damage (90%). Over two-thirds also believed AI-related threats are evolving faster than their ability to adapt, and that failing to adapt networks over the next two years will only increase security risks. At the same time, an observability gap is widening as traditional monitoring tools struggle with bursty, east-west agentic flows. Read more about AI in networking Networks the key in post-Mythos world : Platform offers unified approach for humans and AI agents to run critical IT infrastructure together, allowing customers to build their own apps and agents in natural language. Network readiness a determining factor for AI success : Report reveals how firms are harnessing AI to drive progress and overcome industry challenges, with most expecting ‘significant’ increases in connectivity and reliability demands. Implementation gap threatens progress in AI and 5G : Despite current patchy deployment of key 5G services, study finds that across regions, company sizes and markets, telecoms leaders are strikingly confident about their ability to capture the next wave of growth. Agent ONE takes forward network AI : Network firm launches ‘smarter, faster, autonomous’ approach to enterprise networking, with its operating model moving from assistive AI to autonomous, always-on operations.
- Anthropic's biggest launch
Anthropic's latest launch and its implications for AI leaders
- Sarvam raises $234 million, becomes AI unicorn amid Anthropic curbs
Sarvam has become India's newest AI unicorn after raising $234 million in a Series B funding round led by HCLTech. The post Sarvam raises $234 million, becomes AI unicorn amid Anthropic curbs appeared first on MEDIANAMA .
Score: 70💰 MoneyJun 16, 2026https://www.medianama.com/2026/06/223-sarvam-raises-234-million-ai-unicorn-amid-anthropic-restrictions/ - Is Anthropic Losing Goodwill With AI Researchers?; AGI House Alums Raise $25 Million For New Fund
Is Anthropic Losing Goodwill With AI Researchers?; AGI House Alums Raise $25 Million For New Fund The Information
- Qualcomm CEO says AI agents will replace apps — as chip giant works on 40 new AI-powered devices
Qualcomm CEO Cristiano Amon said he is bullish on smart glasses which could eventually become as big as the smartphone.
- Campaigners Urge G7 Chiefs To Protect Children From AI Risks
Campaigners Urge G7 Chiefs To Protect Children From AI Risks Barron's
Score: 70🌐 MovesJun 16, 2026https://www.barrons.com/news/campaigners-urge-g7-chiefs-to-protect-children-from-ai-risks-baa69709?refsec - Hamilton advances proposed data centre moratorium in pushback to rapid AI buildout
Hamilton advances proposed data centre moratorium in pushback to rapid AI buildout Toronto Star
- Gmail’s AI summaries are live for everyone, but here’s how you can turn them off
No more actually reading email! Gemini does that for you, whether you like it or not.
Score: 70🌐 MovesJun 16, 2026https://www.androidauthority.com/google-gmail-ai-summaries-global-turn-off-3677798/ - Agentic AI is coming to government faster than its guardrails
A former FBI cyber special agent believes we’re having the wrong conversation about artificial intelligence in government. The post Agentic AI is coming to government faster than its guardrails appeared first on FedScoop .
- Europe rearms: Battle management, counter-UAS, and real AI at the edge
Europe rearms: Battle management, counter-UAS, and real AI at the edge Breaking Defense
Score: 70🌐 MovesJun 16, 2026https://breakingdefense.com/2026/06/europe-rearms-battle-management-counter-uas-and-real-ai-at-the-edge/ - Rainbow Crops raises $11.25m to scale AI-guided multiplex gene editing
Rainbow Crops expects to announce a collaboration with a seed company on corn soon and is discussing additional partnerships in other crops. The post Rainbow Crops raises $11.25m to scale AI-guided multiplex gene editing appeared first on AgFunderNews .
Score: 70💰 MoneyJun 16, 2026https://agfundernews.com/rainbow-crops-raises-11-25m-to-scale-ai-guided-multiplex-gene-editing - Google Rolls Out Android 17; Major AI Features to Follow This Summer
Alphabet Inc.’s Google has begun rolling out Android 17, the latest major update to its popular mobile operating system, though some of its marquee artificial intelligence features will not arrive for another few months.
- US and Europe discuss access to AI models after Anthropic dispute
‘Trusted partner’ scheme would allow US allies to test cutting-edge models