AI News Archive: May 28, 2026 — Part 8
Sourced from 500+ daily AI sources, scored by relevance.
- This Sentence About AI Got Apple Co-Founder Steve Wozniak Applause—not Boos—for His Commencement Speech
New grads keep heckling speakers for their comments on AI. But Wozniak told them something they actually wanted to hear.
Score: 10🌐 MovesMay 28, 2026https://www.inc.com/fast-company-2/ai-apple-co-founder-steve-wozniak-applause-commencement-speech/91351548 - Agentic AI & Data Platform Architecture, BlackRock Global Markets, Director
Agentic AI & Data Platform Architecture, BlackRock Global Markets, Director Built In
Score: 09🌐 MovesMay 28, 2026https://builtin.com/job/agentic-ai-data-platform-architecture-blackrock-global-markets-director/9529530 - Director, Solution Architect, AI-Native Engineering
Director, Solution Architect, AI-Native Engineering Built In
Score: 09🌐 MovesMay 28, 2026https://builtin.com/job/director-solution-architect-ai-native-engineering/9529914 - Senior AI DevOps Engineer
Senior AI DevOps Engineer Built In
- Sr. UI Engineer - AI Detection and Response (AIDR) (Hybrid)
Sr. UI Engineer - AI Detection and Response (AIDR) (Hybrid) Built In
Score: 08🌐 MovesMay 28, 2026https://builtin.com/job/sr-ui-engineer-ai-detection-and-response-aidr-hybrid/9536077 - Watch Conan O'Brien joke about AI replacement, Harvard lawsuits
Watch Conan O'Brien joke about AI replacement, Harvard lawsuits USA Today
- ‘Hidden datacentre tax’ costing Irish households millions, report says
Datacentres used 22% of country’s electricity last year, pushing up household bills, study suggests Energy demand by datacentres in Ireland has added hundreds of euros to household electricity bills in a pattern that could be replicated across Europe, according to a report. Ireland’s growing number of datacentres last year used 22% of the country’s electricity, more than all urban homes combined , according to the Central Statistics Office. The equivalent figure in the US and UK is 6% . Continue reading...
Score: 08🌐 MovesMay 28, 2026https://www.theguardian.com/technology/2026/may/28/irish-datacentres-household-bills-electricity - Senior Finance Analytics Engineer, AI Native
Senior Finance Analytics Engineer, AI Native Built In
Score: 07🌐 MovesMay 28, 2026https://builtin.com/job/senior-finance-analytics-engineer-ai-native/9526680 - Artificial intelligence
Artificial intelligence AP News
- Musk Defends AI Ambitions As IPO Reveals Trouble
Musk Defends AI Ambitions As IPO Reveals Trouble Barron's
Score: 00🌐 MovesMay 28, 2026https://www.barrons.com/news/musk-defends-ai-ambitions-as-ipo-reveals-trouble-cd9d1171 - Anthropic Valuation Nears $1 Trillion With Mythos Release Weeks Away
Anthropic Valuation Nears $1 Trillion With Mythos Release Weeks Away Barron's
Score: 00💰 MoneyMay 28, 2026https://www.barrons.com/articles/anthropic-valuation-trillion-mythos-ai-943dd833 - Elon Musk Clarifies SpaceX, Anthropic AI Deal. It's Not As Big As Expected.
Elon Musk clarifies SpaceX's AI compute deal with Anthropic is much shorter than the IPO prospectus implied. Space stocks pare rally. The post Elon Musk Clarifies SpaceX, Anthropic AI Deal. It's Not As Big As Expected. appeared first on Investor's Business Daily .
Score: 00🌐 MovesMay 28, 2026https://www.investors.com/news/elon-musk-clarifies-spacex-anthropic-ai-deal-its-not-as-big-as-expected/ - SpaceX’s $1.75 trillion IPO pitch relies on a lot of AI faith
Welcome to AI Decoded , Fast Company ’s weekly newsletter that breaks down the most important news in the world of AI . You can sign up to receive this newsletter every week via email here . Inside the SpaceX S-1 Black Box SpaceX’s S-1 investor prospectus landed last week , and it proves to be equal parts legitimate satellite connectivity business and AI hopium. The document spends 47% of its time discussing artificial intelligence , describing SpaceX’s addressable market as overwhelmingly AI and AI-related. Based on that, despite having relatively little AI business today, SpaceX hopes to raise somewhere between $75 billion and $80 billion from investors, with the entire company valued at $1.75 trillion. Right now, SpaceX’s Starlink business is its main source of real revenue. Starlink generated $11.4 billion in revenue in 2025, accounting for 61% of the company’s total revenue of $18.7 billion. Based on generally accepted accounting principles (GAAP), that represents a 39% margin (and a 63% margin on earnings before interest, taxes, depreciation, and amortization, or EBITDA.). If SpaceX were judged purely on satellite internet execution, its financial thesis would be solid. SpaceX is known primarily as a rocket-launching company, but its business of launching satellites into orbit is a money loser . The S-1 filed with the SEC shows that the company’s Space division posted an operating loss of $657 million in 2025 on revenue of $4.08 billion, alongside $3 billion in R&D spending. Musk and company nevertheless have big plans for the division. The S-1 describes future revenue streams including rocket travel between cities around the world, asteroid mining, and manufacturing on the moon and Mars. But SpaceX’s main proposition to investors, and its central justification for a $1.75 trillion valuation, is its AI business. (SpaceX acquired Musk’s xAI business in February.) The S-1 states that 93% of its total addressable market of more than $28 trillion comes from AI models, apps, and services. More than 80% of that market ($22.7 trillion) consists of large organizations that may buy access to SpaceX’s Grok AI models in hopes of streamlining business operations. SpaceX believes it can compete with market leaders OpenAI, Anthropic, and Google for a sizable share in the future. That’s pretty big talk for an AI division whose largest revenue stream comes from renting out graphics processing units (GPUs) in its Colossus data centers to rival Anthropic. SpaceX is bringing in $1.25 billion per month ($15 billion annually) from that business, by far the largest component of its AI revenue. If xAI were truly a serious contender in the enterprise AI market, it would presumably be using every bit of compute power available to it. The S-1 acknowledges that xAI, with its flagship Grok model and assistant, controls just 3.4% of the AI market today. And, as the PitchBook analyst Franco Granda recently pointed out, the S-1 leaves unanswered some major questions about the state of SpaceX’s AI business: No Grok subscription numbers : The filing avoids breaking out standalone subscription metrics for the Grok assistant. No X subscription numbers: There are no clear standalone subscription revenue figures for the platform to support the integrated narrative. No developer API revenue: For a company positioning itself at the frontier of AI development, measurable ecosystem revenue from developer APIs is nonexistent. No take rate on 1 gigawatt of deployed compute: SpaceX hypes the scale of its data centers, but the S-1 remains quiet on what software margins or transaction fees it actually captures from that deployed power. So potential SpaceX investors are being asked to take the health and long-term potential of the xAI business largely on faith. “Anyone buying SpaceX above $1.5 trillion is primarily buying the AI thesis,” Granda concluded. OpenAI and Anthropic are also expected to pursue IPOs in the near future, with both companies reportedly targeting valuations around $1 trillion. Unlike SpaceX’s AI division, though, they already have significant revenue to support those ambitions. Anthropic said in February that its annualized revenue run rate had reached $14 billion , while reports say OpenAI’s ARR has climbed to $25 billion . Lack of guidance could make teachers a barrier to AI in school School administrators are eager to integrate AI into curricula and classroom activities, but the burden of making that happen is falling largely on teachers, many of whom have received little training or support. That’s a key finding in a new report from Gallup and the Walton Family Foundation, which found that 60% of K–12 teachers now use AI in their classroom work, while roughly eight in 10 educators report receiving no formal guidance on how to apply these tools to their daily responsibilities. Specifically, 71% of teachers say they’ve received no direction on using AI for coaching or feedback on their own teaching, while 69% are essentially winging it when it comes to using AI for one-on-one student tutoring. The same pattern shows up in tasks like grading (58%) and administrative paperwork (59%). The report suggests that this lack of training and clarity is contributing to teacher burnout. Educators in high-need schools are even less likely to receive support than their peers in wealthier districts, creating a “guidance divide” that mirrors existing educational inequities, the researchers say. At the same time, Gen Z students increasingly expect AI literacy to be a core part of their education, and for AI itself to play a central role in learning. The result could be that AI becomes just another optional digital tool, largely because teachers haven’t been given the support needed to meaningfully integrate the technology into the classroom. The report’s authors argue that this risks preventing AI from becoming the transformative force for personalized instruction that many advocates believe it could be. Pangram will check for AI slop posts in real time on X AI-detector software has a bad reputation. Initially embraced as a way to catch AI-savvy students cheating, these tools quickly became known for flagging legitimate writing as AI-generated. But Pangram may be different. Pangram claims a detection rate above 99.8% for content produced by major AI models, alongside a false-positive rate as low as 1 in 10,000. The company says those results are backed by independent research from the University of Chicago and the University of Maryland. To bring attention to its detector, the Brooklyn-based company started conducting real-time AI slop detection on X in late 2024. Users can tag Pangram in posts they suspect were AI-generated, and the company responds in real time with a verdict such as “fully human written” or “fully AI generated.” (In some instances, the original poster deletes the post after receiving a positive “slop check.”) For Pangram, the feature functions both as effective social media marketing and as a public proof of concept for its technology. It has become a defining part of the company’s online presence, giving users a quick way to check for AI slop amid growing anxiety over the spread of generated content online. More AI coverage from Fast Company: These AI bots want to help fans navigate World Cup host cities Oracle and the AI boom’s hidden debt bomb Pope Leo XIV’s AI encyclical is getting a mixed reception from the tech world Girls Who Code CEO Tarika Barrett says AI skepticism can be a strength Want exclusive reporting and trend analysis on technology, business innovation, future of work, and design? Sign up for Fast Company Premium.
- GreyVibe hackers use ChatGPT, Gemini to power cyberattacks
A likely Russian threat cluster tracked as GreyVibe has been targeting Ukrainian entities with AI-generated lures and a rich set of custom malware tools. [...]
Score: 00🌐 MovesMay 28, 2026https://www.bleepingcomputer.com/news/security/greyvibe-hackers-use-chatgpt-gemini-to-power-cyberattacks/ - The Navy used drones to sink a retired warship
Lessons from the SINKEX are shaping the service’s plans to buy and fight.
Score: 00🌐 MovesMay 28, 2026https://www.defenseone.com/defense-systems/2026/05/navy-used-drones-sink-retired-warship/413818/ - Yoco buys AI-native operating system Dyner
The company acquires Dyner.ai, an AI-native operating system built for restaurants and independent businesses.
Score: 00🌐 MovesMay 28, 2026https://www.itweb.co.za/article/yoco-buys-ai-native-operating-system-dyner/rxP3jMBEbKP7A2ye - Yoco’s Dyner.ai deal ushers in new AI era for South African SMEs
South African fintech Yoco is banking on artificial intelligence (AI) to be the next major growth lever for small businesses. To advance that vision, the commerce platform has acquired Dyner.ai, an AI-native operating system built to help Small and Medium-sized Enterprises (SMEs), particularly restaurants, streamline operations. In an interview with TechCabal on Thursday, Carl Wazen, […]
Score: 00🌐 MovesMay 28, 2026https://techcabal.com/2026/05/28/yocos-dyner-ai-deal-ushers-in-new-ai-era-for-south-african-smes/ - Claude’s new model is more ‘honest’ when it messes up
Anthropic is releasing Claude Opus 4.8 on Thursday, and the company is touting the model's "honesty." According to Anthropic, it trains "all [its] models to be honest - for instance, to avoid making claims that they can't support." But it notes that "a general problem with AI models is that they sometimes jump to conclusions, […]
Score: 00🤖 ModelsMay 28, 2026https://www.theverge.com/ai-artificial-intelligence/939094/anthropic-claude-4-8-opus-honesty-effort - Russia-Linked ‘GreyVibe’ Attackers Use AI to Supercharge Cyberattacks
Researchers warn GreyVibe’s extensive use of ChatGPT, Gemini, and other AI tools offers a glimpse into how future cybercriminal and state-aligned groups will operate. The post Russia-Linked ‘GreyVibe’ Attackers Use AI to Supercharge Cyberattacks appeared first on SecurityWeek .
Score: 00🌐 MovesMay 28, 2026https://www.securityweek.com/russia-linked-greyvibe-attackers-use-ai-to-supercharge-cyberattacks/ - Anthropic Customers Creeped Out by Its Newest Models
They're terrified of being shut out. The post Anthropic Customers Creeped Out by Its Newest Models appeared first on Futurism .
Score: 00🌐 MovesMay 28, 2026https://futurism.com/artificial-intelligence/anthropic-customers-creeped-out-models - Anthropic is preparing a major multilingual upgrade for Claude Voice Mode
Claude’s Voice Mode is finally learning multiple languages, and you can reportedly switch just by asking.
Score: 00🌐 MovesMay 28, 2026https://www.androidauthority.com/claude-voice-mode-adding-more-languages-3671980/ - How the Pentagon plans to spend $50 billion on drone warfare
As new drone startups proliferate, Pentagon and military leaders outline their priorities for building “drone dominance."
Score: 00🌐 MovesMay 28, 2026https://www.defenseone.com/technology/2026/05/how-pentagon-plans-spend-50-billion-drone-warfare/413805/ - Waymo launches services with cheaper robotaxis in Los Angeles
Waymo unveils the Ojai, its new self-driving taxi that has more leg room and is better equipped for snowy roads. The rollout begins in Los Angeles, San Francisco and Phoenix.
Score: 00🌐 MovesMay 28, 2026https://www.latimes.com/business/story/2026-05-28/waymo-launches-services-with-cheaper-robotaxis-in-los-angeles - Waymo is rolling out a robotaxi built for bad weather. Tahoe looms ahead
Waymo is rolling out a robotaxi built for bad weather. Tahoe looms ahead San Francisco Chronicle
Score: 00🌐 MovesMay 28, 2026https://www.sfchronicle.com/sf/article/waymo-tahoe-ojai-weather-22278798.php - AIAI.com | Office Floor Plan Generator
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- Segmental Lung Sound Analysis in Obstructive Lung Diseases Using Electronic Stethoscope; a protocol to establish an acoustic repository
Introduction Obstructive lung diseases (OLDs) are responsible for high rates of illness and death worldwide. Inflammation, chronic airflow limitation, and bronchial remodeling occur in OLD and eventually result in the unique respiratory sounds. Despite its subjective and having low reproducibility, still traditional auscultation using a manual stethoscope is the main method used to identify the lung sounds. Nevertheless, the combination of recent advancements in digital stethoscopes and AI (Artificial Intelligence) has permitted the objective measurement of lung sounds. Nevertheless, there is a lack of standardized, region-specific databases for AI training and validation. Even though lung sound classification is an emerging aspect in research and telerehabilitation the lobar wise acoustic pattern is still novel due to lack of prevailing database to train AI models. Identifying this gap this study aims to develop an acoustic repository and analyze the data using segmental lung sounds from patients with OLDs and healthy controls through an electronic stethoscope. Methods and analysis This is a cross sectional observational study involving 120 participants (60 OLD patients and 60 healthy controls). Lobar wise acoustic signals will be captured using an electronic stethoscope in healthy and diseases population. The data will be analyzed using Audacity software for annotations and then it will be used for feature extraction and statistical analysis. The acoustic features extracted through Audacity, will include frequency, intensity, pitch, and root mean square (RMS) energy. Repeated measures ANOVA will be applied to compare mean sound intensities across lung segments while Pearson correlation will be used to assess associations with body composition parameters. The data will then be standardized for AI-based diagnostic applications. Ethics and dissemination The study is being reviewed from the Ethics Review Committee, Faculty of Medicine, University of Peradeniya (2025/EC/87) will be sought. Informed consent will be obtained in writing. The dissemination of results will take place through peer-reviewed publications and the creation of a public database containing lung sounds from the region.
- Generation and Evaluation of Realistic Synthetic Clinical Progress Notes for Prostate Cancer using Large Language Models.
Background and Objective: Access to real-world electronic health records (EHRs) remains limited by privacy, governance and annotation constraints, hindering the development of clinical natural language processing models. Realistic synthetic progress notes may provide EHR-like corpora that preserve clinically rigorous information on diagnoses, treatments, symptoms, imaging, laboratory findings and therapeutic trajectories without relying directly on sensitive patient records. This study evaluates whether large language models (LLMs) can generate realistic Spanish prostate cancer progress notes from published case reports, preserving clinical content, temporality and hospital-style conventions.
- Beyond Identifier Matching: An Empirical Characterization of Failure Modes in Biomedical Knowledge Graph Integration
Objective. Biomedical knowledge graphs (KGs) such as PrimeKG, Hetionet, UMLS, and PharmGKB are increasingly used as the substrate for downstream machine-learning, retrieval-augmented generation, drug-repurposing, and electronic health record (EHR) augmentation pipelines. The dominant assumption in published work is that integrating two or more such KGs is a tractable engineering step solved by identifier (ID) matching. This paper interrogates that assumption empirically. We quantify how much concept overlap survives realistic alignment, and we characterize the new failure modes introduced by the methods that practitioners reach for when ID matching is insufficient. Materials and Methods. We compared four widely used biomedical KGs (PrimeKG, Hetionet v1.0, the full UMLS Metathesaurus, and PharmGKB) across eleven node types using a tiered alignment pipeline: (1) direct ID matching for nodes sharing a primary vocabulary; (2) cross-ontology bridging using standard mappings (e.g., MONDO-DOID, HPO-UMLS, HPO-UMLS-MeSH for side effects, NCBI Gene-HGNC-UMLS, UBERON-FMA/SNOMEDCT_US/NCI/MeSH for anatomy); (3) ClinicalBERT cosine-similarity grouping at threshold >= 0.98 for over-segmented disease nodes, with a deterministic suffix-stripping canonicalizer; (4) exact name matching for ontology-poor types (anatomy, REACTOME pathways); and (5) embedding-based fuzzy matching with UMLS lookup (SapBERT and ClinicalBERT) for free-text microbiome concepts. We applied the pipeline to a 698-concept gut-microbiome benchmark spanning taxa, pathways, and disease labels, validated grouping decisions against the curated SSSOM mappings released by the MONDO project, and audited the ClinicalBERT consolidation against five clinical-genetics case studies drawn from the literature. Results. Per-type pairwise coverage was strikingly asymmetric. Genes/proteins and the three Gene Ontology categories aligned cleanly across PrimeKG and Hetionet (mutual coverage 94-99%), but disease overlap was sparse: only 0.7% of PrimeKG individual disease nodes mapped to Hetionet, rising to 2.0% after MONDO grouping (versus 78.7% and 18.4% from the Hetionet side). PrimeKG-to-UMLS coverage spanned 100% (effect/phenotype via HPO) down to 20.8% (REACTOME pathways), with drugs at 73.7% and anatomy at 58.8%. PrimeKG-to-PharmGKB drug coverage required up to two bridging hops (DrugBank -> UMLS -> RxNorm/ATC/MeSH). Bigger was not uniformly more complete: on a 698-concept microbiome drug benchmark, Hetionet missed 0 concepts while PrimeKG missed 16. ClinicalBERT-based grouping consolidated 22,205 raw MONDO disease nodes into 17,080 groups but introduced three reproducible failure modes documented in case studies: (i) peer over-merging: for example, all 22 osteogenesis imperfecta subtypes collapsed into a single node despite distinct severity classes; (ii) parent-child collapse: e.g. acute myeloid leukemia merged with myeloid leukemia, erasing the acute/chronic distinction that drives clinical management; and (iii) lexical false positives: neurofibromatosis and schwannomatosis grouped together despite cellular-pathology differences. Discussion. Identifier matching alone is a weak baseline for biomedical KG integration. Cross-ontology bridges and embedding-based consolidation expand coverage but do so at the cost of clinically meaningful resolution, and the resulting failures are systematic rather than random. Reporting only aggregate coverage statistics obscures these losses, which propagate silently into downstream tasks. Conclusion. We provide reusable per-type coverage tables, a taxonomy of three integration failure modes, and concrete recommendations for downstream studies that depend on a unified biomedical KG. We argue that future KG integration work should report per-type coverage and per-cluster confidence rather than aggregate match rates.
- Tobacco Use is Related to Parietal-Hippocampal Connectivity in People at Clinical High Risk for Psychosis
Background: Tobacco use is prevalent in clinical high risk for psychosis (CHR-P) population and has widespread negative health consequences, but understanding of its neural substrates is limited. Abnormal default mode network (DMN) may underlie tobacco dependence in CHR-P. We investigated how tobacco use relates to DMN connectivity and how CHR-P status impacts this relationship. Methods: We used baseline substance use and resting-state functional magnetic resonance imaging data from the North American Prodrome Longitudinal Study (NAPLS2; CHR-P: n=211, mean age 19.2, 37.9% female; healthy control: n=132, mean age 19.9, 47.7% female). Voxel-wise connectivity was calculated from the left lateral parietal (LLP) node of the DMN to the rest of the brain. We regressed LLP-brainwide connectivity against tobacco use frequency in the past month to generate a spatial map of how connectivity relates to current tobacco use. Results: Brainwide connectivity analysis identified two clusters in R hippocampus (peak voxel at MNI [+30,-12,-27]) and in L parahippocampus (peak voxel at MNI [-27,-27,-27]), where higher LLP-cluster connectivity was associated with more frequent tobacco use. LLP - R hippocampus connectivity was higher in current tobacco users compared to non-tobacco users (t=-3.5466, df=101.88, p=0.0006), and higher in CHR-P than controls (t=-2.8651, df=279.47, p=0.0049). Among current tobacco users, there was a significant tobacco-by-diagnosis interaction on LLP - R hippocampus connectivity (estimate=0.306, SE=0.149, t=2.051, p=0.045) such that heavier tobacco use predicted hyperconnectivity only in CHR. Conclusions: More frequent tobacco use was associated with higher DMN-hippocampal connectivity in both CHR-P and controls. CHR-P diagnosis enhanced this relationship.
- Illinois Lawmakers Just Passed America’s Strongest AI Safety Bill
The bill requires companies like OpenAI, Anthropic, and Google to have third parties confirm they’re following safety standards. Illinois governor JB Pritzker says he’ll sign it.
- Trump loses more control over AI regulation as Illinois passes landmark law
Here’s why Anthropic and OpenAI are on board with Illinois safety testing.
- New details on Apple-Google AI deal revealed, including Nvidia chips: report
Apple’s big unveiling of iOS 27, the new Siri, and other WWDC reveals are little more than one week away . And today, a new report has fresh details on how Apple’s partnership with Google for AI features is being implemented behind the scenes. more…
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