AI News Archive: June 22, 2026 — Part 2
Sourced from 500+ daily AI sources, scored by relevance.
- G42’s Inception rebrands as Inception42 to accelerate UAE’s sovereign AI ambitions – EXCLUSIVE
G42’s Inception rebrands as Inception42 to accelerate UAE’s sovereign AI ambitions – EXCLUSIVE Arabian Business
- AI-Services Startup Baseten Nabs $13 Billion Valuation
Baseten, which provides software and computing capacity to companies tapping into lower-cost AI models, just closed a $1.5 billion Series F round at a $13 billion valuation. Baseten CEO Tuhin Srivastava and Apoorv Agrawal, partner at Altimeter, which co-lead this round, sit down with Ed Ludlow on "Bloomberg Tech." (Source: Bloomberg)
Score: 78💰 MoneyJun 22, 2026https://www.bloomberg.com/news/videos/2026-06-22/ai-services-startup-baseten-nabs-13-billion-valuation-video - Boruikang Files for IPO as China's First Brain-Computer Interface Public Company
Boruikang, behind the world's first approved invasive BCI medical device, files for STAR Market IPO to fund further R&D and commercialization.
- Exclusive: The AI company powering public safety operations for the 2026 World Cup just raised $250 million
Exclusive: The AI company powering public safety operations for the 2026 World Cup just raised $250 million Fortune
- Tesla Driver Says He Used Driver-Assistance In Fatal Crash — Sparking Federal Probe
A driver in Texas claimed he was using his Tesla’s driver-assistance feature when it crashed into a home at a high speed.
- Three things to watch amid Anthropic’s latest feud with the government
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. For those of you enjoying your summer unaware of Anthropic’s latest feud with the US government, here’s a recap: In April the company said it had built an AI model called Mythos…
- Import AI 462: Superpersuasion; self-sustaining AI; paths to ASI
How religious are beliefs in the singularity?
- Qualcomm Nears Deal for AI Chip Startup Modular
Qualcomm Inc. is in advanced talks to acquire Modular Inc. in a transaction valuing the artificial intelligence infrastructure software company at about $4 billion, according to people familiar with the matter.
Score: 77💰 MoneyJun 22, 2026https://www.bloomberg.com/news/articles/2026-06-22/qualcomm-is-said-to-near-deal-for-ai-chip-startup-modular - California AG Announces $7M Settlement in ‘Algorithmic Rent Scheme’
A property management company is paying $7 million for what the California Attorney General calls an “algorithmic rent alignment scheme.” California Attorney General Rob Bonta worked on the settlement as part of a coalition of nine attorneys general with LivCor …
- Strategy for Post-Exascale: Shaping the European Union future of HPC, AI and Quantum
Europe is preparing for the next frontier of computing with the launch of the Strategy for Post Exascale (SPE) project. Coordinated by Inria, SPE brings together 23 leading organisations to build a dynamic European vision for the convergence of High-Performance Computing (HPC), Artificial Intelligence (AI) and Quantum Computing Systems (QCS) from 2026 to 2029, strengthening and paving the way for Europe’s leadership in the post-Exascale era. The project started in April 2026 and officially launched on 10 June during its kick-off meeting at the Campus Cyber, in Paris La Défense.
- Samsung rolls out ChatGPT Enterprise and Codex to employees in South Korea
Samsung Electronics is deploying ChatGPT Enterprise and Codex to all employees in South Korea and everyone in its Device eXperience (DX) division worldwide. The article Samsung rolls out ChatGPT Enterprise and Codex to employees in South Korea appeared first on The Decoder .
Score: 77🌐 MovesJun 22, 2026https://the-decoder.com/samsung-rolls-out-chatgpt-enterprise-and-codex-to-employees-in-south-korea/ - Apple supplier Lingyi seeks US$1.1 billion Hong Kong IPO to fund AI and robotics push
Apple supplier Lingyi iTech is looking beyond smartphones, seeking to raise up to HK$8.3 billion (US$1.1 billion) in a Hong Kong initial public offering (IPO) to fund an ambitious expansion into artificial intelligence hardware and humanoid robotics. The Shenzhen-listed electronic components maker is expected to debut on the Hong Kong stock exchange on Friday after offering 811.8 million shares at a maximum price of HK$10.18 each, according to a company filing. The subscription period opened...
- Zhipu AI market cap tops HK$1 trillion as shares of GLM-5.2 developer soar
The market capitalisation of Hong Kong-listed artificial intelligence pioneer Zhipu AI surpassed HK$1 trillion (US$128 billion) on Monday, fuelled by investor optimism as the company goes head-to-head with its American rivals. Shares of Zhipu, which trades under the name Knowledge Atlas Technology, skyrocketed as much as 42 per cent on Monday morning to a peak of HK$2,980. They subsequently retreated to a gain of 15.1 per cent, ending the day at HK$2,410. The stock has now surged more than 1,700...
- Prosper AI lands $30M backed by Andreessen Horowitz to build AI workforce for healthcare operations
Prosper AI banked $30 million to scale its agentic AI platform to power administrative tasks from patient scheduling to insurance verification and patient billing.
- Exclusive: Upscale AI wants to be the next Cisco—and it just raised another $190 million
Exclusive: Upscale AI wants to be the next Cisco—and it just raised another $190 million Fortune
Score: 77💰 MoneyJun 22, 2026https://fortune.com/2026/06/22/nvidia-upscale-ai-next-ciscoand-seligman-ventures-premji/ - Data-Driven Representation and Reasoning for Aviation Safety
Data-Driven Representation and Reasoning for Aviation Safety Robotics Institute Carnegie Mellon University
Score: 76🌐 MovesJun 22, 2026https://www.ri.cmu.edu/event/data-driven-representation-and-reasoning-for-aviation-safety/ - Waymo Issues Another Recall, This Time Over Highway Construction Zones
The robotaxi company issues a recall on 3,871 vehicles that could make incorrect decisions while driving in highway construction zones.
Score: 76🌐 MovesJun 22, 2026https://www.cnet.com/roadshow/news/waymo-recall-highway-construction-zones/ - South Korea turns to AI as personnel shortage strains military medical system
South Korea’s military has begun work on a plan to incorporate artificial intelligence into its medical system, as a sharp decline in military doctors raises concerns over the sustainability of its professional personnel-driven healthcare structure. According to military officials Monday, the Armed Forces Medical Command recently commissioned a policy research project to draw up a long-term development plan for AI-based military medicine. The move comes as the military faces growing pressure to
- NAIRR Science Program Reshapes Scientific Research, Powered by NVIDIA AI Infrastructure
For the past two years, the U.S. National Science Foundation’s National Artificial Intelligence Research Resource (NAIRR) pilot program has driven innovative research across the U.S. for over 700 projects — spanning protein prediction and infectious disease outbreak management. NVIDIA contributed to the NAIRR pilot through a cloud-based resource that gives researchers dedicated access to a […]
Score: 76🌐 MovesJun 22, 2026https://blogs.nvidia.com/blog/nairr-scientific-research-ai-infrastructure/ - Government urged to abandon plans to use AI age checks for child asylum seekers
Government urged to abandon plans to use AI age checks for child asylum seekers Computing UK
- Anthropic will pay workers $85,000 to learn AI — and it reveals the next big AI job trend
Anthropic will pay workers $85,000 to learn AI — and it reveals the next big AI job trend Tom's Guide
- OpenAI signs deal to show Getty's images in ChatGPT results
Getty Images will allow OpenAI to use its content library in AI search and ChatGPT.
Score: 75🌐 MovesJun 22, 2026https://www.engadget.com/2198633/openai-signs-deal-with-getty-to-show-images-in-chatgpt-results/ - How indigenous AI capabilities can strengthen India’s security and strategic autonomy
By Kaushal Bheda, Director of GovTech, Pelorus Technologies On 12 June 2026, one of the world’s leading AI companies disabled access to its two most advanced models for every customer […] The post How indigenous AI capabilities can strengthen India’s security and strategic autonomy appeared first on Express Computer .
- Getty Images strikes multi-year deal to put licensed photos in ChatGPT search
Getty Images has entered into a multi-year licensing agreement with OpenAI. The article Getty Images strikes multi-year deal to put licensed photos in ChatGPT search appeared first on The Decoder .
Score: 75🌐 MovesJun 22, 2026https://the-decoder.com/getty-images-strikes-multi-year-deal-to-put-licensed-photos-in-chatgpt-search/ - Claude Fable 5 Blocked for Non-US Users: Why Domestic AI Is the Only Safe Bet for China
The US government's sudden order blocking foreign access to Anthropic's Claude Fable 5 signals a new era of AI export control, reinforcing the strategic importance of China's domestically developed AI models.
- Zhipu AI Breaches Trillion Yuan Market Cap: What Is Driving the Surge?
Zhipu AI's Hong Kong-listed shares surged past HKD 2,380, pushing its market capitalization beyond HKD 1 trillion. A deep dive into the fundamentals, market dynamics, and risks behind the stunning valuation.
- OpenAI’s $100 billion ad bet
The tech giant rolled out new tools for creatives.
- Microsoft’s Satya Nadella: We Can’t Let AI Giants Eat the Economy
Microsoft’s CEO offers a blistering critique of the AI power balance and calls for earning society’s permission.
- Workday must face California lawsuit over AI bias in job screening tools
Workday must face California lawsuit over AI bias in job screening tools Reuters
- Researchers introduce Self-Harness, a framework that lets AI agents rewrite their own rules, boosting performance up to 60%
Not every company can or should build their own frontier AI language model. However, the harness controlling the model is something that most enterprises can and should customize for their specific purposes. Of course, this is easier said than done. A gent harnesses are still largely tuned through manual, ad hoc debugging — a process that relies heavily on intuition rather than systematic feedback loops, making it difficult to keep pace with rapidly evolving LLMs. To solve this challenge, researchers at the Shanghai Artificial Intelligence Laboratory have introduced “ Self-Harness ,” a new paradigm in which an LLM-based agent systematically improves its own operating rules. By examining its own execution traces to apply edits, the system trades manual guesswork for empirical evidence. Self-improving harnesses can enable development teams to deploy robust custom agents that continually adapt their own execution protocols to overcome model-specific weaknesses. The challenge of harness engineering An LLM-based agent's performance is not determined solely by its underlying base model, but also by its harness: the surrounding system that provides context and enables the model to interact with the environment. A harness includes components like system prompts, tools, memory, verification rules, runtime policies, orchestration logic, and failure-recovery procedures. This layer is crucial because many common agent failures stem from the harness rather than the model. For example, an agent may report success without checking the model’s response (e.g., running the code to see if it passes the tests), or it might retry a failed action repeatedly. The harness is also responsible for preventing context rot or overload when the agent’s interaction history grows very large. Examples of popular harnesses include SWE-agent, Claude Code, Codex, and OpenHands. Harness engineering remains a significant challenge, but the bottleneck isn't necessarily that humans are too slow or incapable. In fact, Hangfan Zhang, lead author of the Self-Harness paper, told VentureBeat that "in many cases, an experienced engineer with deep domain knowledge can still propose better changes than an LLM can today." Instead, the true bottleneck of manual engineering is that it relies heavily on ad hoc debugging rather than a verifiable, empirical feedback loop. "The deeper issue is that the current harness-engineering paradigm often lacks a systematic feedback loop," Zhang explained. "Many edits are made based on intuition, a few observed failures, or ad hoc debugging." With new models being released at a rapid pace, depending on human intuition to manually tune model-specific harnesses becomes increasingly costly and untenable. While some approaches use stronger models to improve the harnesses of weaker target agents, this dependence on external guidance has its own challenges, as these models may be costly, unavailable for frontier models, or mismatched to the target model's failure modes. How Self-Harness works The Self-Harness paradigm enables an LLM-based agent to improve its own harness without relying on human engineers or stronger external models. This continuous self-evolution is driven by a three-stage iterative loop that turns behavioral evidence into harness updates: Weakness mining: Starting from an initial harness, the agent runs a set of tasks, producing execution traces with verifiable outcomes. The agent categorizes failed traces and tries to detect model-specific failure patterns. Harness proposal: Based on these failure patterns, the agent uses a “proposer” role to generate a set of diverse yet minimal harness modifications, each tied to a specific failure mechanism to avoid overly general corrections. Proposal validation: The system evaluates candidate modifications through regression tests. An edit is promoted only if it improves performance without causing measurable degradation on held-out tasks. If multiple candidate modifications pass the regression tests, they are merged into the next version of the harness, which then serves as the starting point for the next iteration. To visualize why an enterprise would need this, imagine an automated issue-fixing agent that reads internal documentation, writes patches, and opens pull requests. If the company updates its documentation style, the agent might suddenly fail, pulling the wrong context or writing bad patches. On the surface, the agent simply looks broken. But Self-Harness turns this ambiguous failure into a solvable problem. "The failure traces expose where the agent is misusing the new documentation format; the proposer can generate a targeted harness edit... and the evaluator can decide whether that edit improves the failing cases without regressing other cases," Zhang said. Self-Harness in action The researchers evaluated Self-Harness on Terminal-Bench-2.0 , a benchmark that tests general tool-based execution, including artifact management, command use, verification behavior, and recovery from execution errors. They applied Self-Harness with MiniMax M2.5, Qwen3.5-35B-A3B, and GLM-5. To isolate the impact of the self-evolving harness, they started with a minimal harness built upon the DeepAgent SDK, containing only the benchmark-facing system prompt, and the default filesystem and shell tools. The model backend, tool set, benchmark environment, and evaluator were kept unchanged while only the harness was allowed to vary. The quantitative results show that agents improved their performance through automated harness edits. On held-out tasks, performance jumped significantly across the board, ranging from 33 to 60 percent relative improvements for different models. Importantly, an explicit acceptance rule promotes only those edits that improve performance without introducing unacceptable regressions. What makes Self-Harness powerful for enterprise applications is that it doesn’t simply make the prompt longer or add generic instructions. Instead, it introduces targeted changes that reflect the recurring problems each model encounters during execution. For example, under the baseline harness, MiniMax M2.5 would get stuck endlessly exploring dataset configurations until the execution environment timed out, failing to produce any deliverables. Through Self-Harness, the system identified this specific flaw and wrote a "loop breaker" into its runtime policy, forcing the agent to stop and redirect its approach after 50 tool calls. It also added a rule to create an initial version of required artifacts as early as possible. On the other hand, Qwen-3.5 had a habit of hitting a file overwrite error and then blindly retrying the same command repeatedly, eventually deleting necessary files out of confusion before stopping. The self-harness fixed this by introducing a strict command-retry discipline (forbidding exact duplicate commands) and a mechanism that forced the agent to immediately recreate any missing artifacts if a file error occurred. GLM-5 struggled to preserve environment changes across different commands, and would often waste time on massive downloads or finalize tasks even when sanity checks were failing. Its self-generated harness introduced rules instructing the agent to persist PATH variables across shell sessions, limit external compute, and repair any failed sanity checks before concluding its run. The hidden costs of automated harnesses While Self-Harness automates the tedious work of tracking down idiosyncratic model failures, decision-makers must be realistic about the trade-offs. Replacing human engineering with automated trial-and-error requires significant computational overhead. "Self-Harness replaces part of the human engineering burden with repeated proposal generation, parallel candidate evaluation, and regression testing," Zhang said. "That can mean more API tokens, more latency during optimization, and more infrastructure for running evaluation tasks." Also, this system relies on the accuracy of its evaluation pipeline. During their experiments on Terminal-Bench-2.0, the researchers relied on strict, deterministic verifiers to ensure the agent's edits were actually helpful. Without this rigorous ground truth, an automated system risks promoting bad updates. "[The] evaluation system is not an optional component; it is what lets us trade human intuition for empirical evidence," Zhang said. This reliance on strict verifiers also dictates where Self-Harness should be deployed. "The best deployment targets today are environments where failures can be measured and where trial-and-error is relatively safe," Zhang said, pointing to coding, internal workflow automation, and DevOps data pipelines as ideal use cases. Conversely, enterprises should avoid fully automating harnesses in high-stakes or subjective fields. "The clearest red flags are domains where evaluation is subjective, delayed, non-deterministic, or costly to get wrong, such as medical decision-making, safety-critical infrastructure, or legal decisions." From prompt tweakers to feedback architects The introduction of self-improving agents does not mean coding or enterprise workflows will suddenly become human-free. The quality of collaboration between the human engineer and the AI is still paramount and difficult to capture with automated benchmarks. Instead, the engineering profession is moving up the abstraction layer. "The role of enterprise engineers will shift from manually patching individual prompts or tool calls toward designing the feedback systems that make agent improvement possible," Zhang predicted. Moving forward, "the engineer becomes less of a prompt tweaker and more of a feedback architect." As foundational models grow more capable, they will naturally absorb many capabilities that currently require manual harness engineering. "But once that happens, the harness will not disappear; its scope will move outward to connect the model to richer external environments," Zhang said. "Until that boundary moves beyond what humans can evaluate, humans will remain critical providers of feedback."
- How Anthropic may have talked itself into an AI export ban
The company warned about dangers of advanced AI far more than rival OpenAI.
Score: 75🌐 MovesJun 22, 2026https://arstechnica.com/ai/2026/06/how-anthropic-may-have-talked-itself-into-an-ai-export-ban/ - Head of Microsoft Rages at His Fellow CEOs for Admitting What They’re Actually Doing to Society With AI
"We now have to do the hard work in earning the social permission." The post Head of Microsoft Rages at His Fellow CEOs for Admitting What They’re Actually Doing to Society With AI appeared first on Futurism .
Score: 74🌐 MovesJun 22, 2026https://futurism.com/future-society/microsoft-ceo-satya-nadella-ai-society - S. Korean, Indian FMs to discuss economy, AI, defense ties this week
Foreign Minister Cho Hyun plans to meet his Indian counterpart in Seoul this week to discuss ways to enhance bilateral cooperation in the economy, defense, artificial intelligence and other key areas, Seoul's foreign ministry said Monday. Cho is scheduled to hold talks with Indian External Affairs Minister Subrahmanyam Jaishankar in Seoul on Wednesday during the top Indian diplomat's official visit to South Korea following his trip to Mongolia, according to the ministry. At the upcoming meeting,
- Leaf4Life Engages Phase Advance To Predict Clinical Outcomes for 16 Phase 3 Trials
Leaf4Life Engages Phase Advance To Predict Clinical Outcomes for 16 Phase 3 Trials azcentral.com and The Arizona Republic
- BP, Marathon, 7-Eleven, Walmart sued for allegedly using AI to boost California gas prices
BP, Marathon, 7-Eleven, Walmart sued for allegedly using AI to boost California gas prices Reuters
- Seedcamp eyes physical AI with $320M raise
Seedcamp eyes physical AI with $320M raise PitchBook
Score: 74💰 MoneyJun 22, 2026https://pitchbook.com/news/articles/seedcamp-eyes-physical-ai-with-320m-raise - Microscopic image changes can bypass AI guardrails, nearly doubling unsafe responses
It may look like a picture of a panda bear to you, but to your business's AI agent, it can act like a skeleton key, bypassing safety safeguards and potentially causing the model to generate harmful, misleading or policy-violating outputs.
Score: 74🌐 MovesJun 22, 2026https://techxplore.com/news/2026-06-microscopic-image-bypass-ai-guardrails.html - FIFA World Cup 2026: A test bed for AI infrastructure and smart cities
FIFA World Cup 2026: A test bed for AI infrastructure and smart cities
- Nvidia gets all agentic about supercomputing for scientific research
Tireless AI agents could help scientists do research humans alone can't, says GPU giant
- Alphabet sees $269B market-cap wipeout amid fears it’s losing the AI talent war
Alphabet sees $269B market-cap wipeout amid fears it’s losing the AI talent war
Score: 73🌐 MovesJun 22, 2026https://www.marketwatch.com/bulletins/redirect/go?g=a2a0e390-8ac1-40f8-a264-3818c0465a6e&mod=mw_rss_bulletins - Hotter Than a Hot Tub: The 45°C Breakthrough to Cool AI’s Biggest Machines
Hot tubs sit at about 38 to 40 degrees Celsius, warm enough that most people can only soak for about 15 minutes. NVIDIA’s newest AI servers can run their cooling liquid even hotter — up to 45 degrees Celsius, or 113 degrees Fahrenheit. That higher temperature limit is precisely what makes them more energy efficient. […]
- World Model AI Lab Odyssey Now Valued at $1.45B
The vendor is among a group of well-financed startups developing physical AI models.
Score: 73💰 MoneyJun 22, 2026https://aibusiness.com/generative-ai/world-model-ai-lab-odyssey-valued-at-1-45-billion - EXCLUSIVE Indonesia plans to embed AI in key programmes, including $15 billion free-meal drive, document shows
EXCLUSIVE Indonesia plans to embed AI in key programmes, including $15 billion free-meal drive, document shows Reuters
- South Korea exports hit record $62b on AI chip surge
Semiconductor exports nearly tripled to US$25.5 billion and made up 41.2% of total shipments.
Score: 72🌐 MovesJun 22, 2026https://www.techinasia.com/semiconductors-power-koreas-67-5b-export-jump - Tencent tests AI assistant in China's most popular app as it looks to catch up with rivals
WeChat is an indispensable part of daily life in China and Tencent is trying to tap into its huge user base to expand use of its AI services.
- Norway to sharply restrict AI use in schools, bring back more books in classrooms
Norway will impose strict limits on the use of generative AI in schools starting in the new academic year in… The post Norway to sharply restrict AI use in schools, bring back more books in classrooms appeared first on MEDIANAMA .
Score: 72🌐 MovesJun 22, 2026https://www.medianama.com/2026/06/223-norway-restrict-ai-use-schools-bring-back-books-classrooms/ - China's push for green power use in AI projects faces hurdles, experts say
China's push for green power use in AI projects faces hurdles, experts say Reuters
- Sakana AI's Fugu orchestrates multiple LLMs to match Anthropic's Fable and Mythos benchmarks
Japanese AI startup Sakana AI is launching Fugu, a system that coordinates multiple AI models on the fly to compete with leaders like Anthropic's Fable 5. The approach also aims to cut dependence on any single AI provider. The article Sakana AI's Fugu orchestrates multiple LLMs to match Anthropic's Fable and Mythos benchmarks appeared first on The Decoder .
- Wikipedia Won't Let AI Edit Articles, Cofounder Says
Wikipedia Won't Let AI Edit Articles, Cofounder Says Barron's
Score: 72🌐 MovesJun 22, 2026https://www.barrons.com/news/wikipedia-won-t-let-ai-edit-articles-cofounder-says-a56da8c5 - Lyft CEO: we’re setting a multi-sensor safety standard for autonomous rides
Lyft CEO: we’re setting a multi-sensor safety standard for autonomous rides Fortune
Score: 72🌐 MovesJun 22, 2026https://fortune.com/2026/06/22/lyft-ceo-multi-sensor-autonomous-vehicle-safety-standard/