AI News Archive: July 23, 2026 — Part 7
Sourced from 500+ daily AI sources, scored by relevance.
- Ask the Analyst: AI in Bank Lending and Trade Finance
Ask the Analyst: AI in Bank Lending and Trade Finance Gartner
- Consumer distrust of AI isn’t all about the AI
Research shows consumers worry less about the technology than how brands collect, manage, and use their personal data. The post Consumer distrust of AI isn’t all about the AI appeared first on MarTech .
- AI success requires a full-stack CIO
Every CIO I speak with today is wrestling with some version of the same question: How do we move faster with AI and deliver on our commitments? It’s an understandable concern. Boards and CEOs are asking about AI . Business leaders are experimenting with use cases. Employees are discovering tools daily, while technology vendors promise unprecedented gains in productivity, innovation, and competitive advantage. After hundreds of conversations with technology executives over the past year, I’ve become convinced that speed isn’t the real issue. The organizations pulling away from the pack aren’t necessarily adopting AI faster than everyone else. They’re executing more effectively — a subtle distinction that represents one of the defining leadership challenges of the AI era. Technology has never been the hardest part of transformation. People, priorities, culture, and operating models are the biggest challenges. The ability to translate bold boardroom aspirations into thousands of thoughtful decisions made every day by architects, engineers, product managers, analysts, and business leaders is where competitive advantage is created. AI may be accelerating the pace of change, but it hasn’t changed that fundamental truth. I’ve met plenty of executives who are exceptional in the boardroom. They know how to frame a vision, influence a board , and build confidence among investors and business leaders. I’ve also met remarkable technologists who instinctively understand the architectural decisions, engineering tradeoffs, and implementation details that determine how great ideas become reality. Modern CIOs, however, must move comfortably between both worlds. Afshean Talasaz is one who stands out among this rare breed. Long before becoming CIO of Colonial Pipeline, Talasaz built his career from the ground up as a business professional, data scientist, and technologist. He has designed enterprise platforms, built AI capabilities, led technology organizations, and partnered closely with executive leadership teams on business transformation. Today, as an executive in residence with our Practitioners for Practitioners (P4P) community, he helps CIOs and business leaders navigate one of the most significant technology shifts of our generation. While Talasaz brings deep knowledge of data and AI to the table, his greatest strength is his ability to create strategy and connect it with execution. He can spend the morning discussing enterprise reinvention with the board and the afternoon debating architectural principles with the teams responsible for bringing that vision to life. That versatility gives Talasaz a unique lens on how CIOs can deliver value with AI . Software companies have a term for engineers who understand every layer of the technology stack: full-stack developers. Listen to Talasaz and it becomes evident that the AI era requires something similar from technology leaders: a full-stack CIO. The full-stack CIO: Leading with clarity A full-stack CIO understands how every layer of the enterprise influences the next. They recognize that every strategic priority becomes a portfolio investment, every investment shapes an operating model, every operating model influences architecture, every architecture choice informs product decisions, every product decision shapes engineering priorities. The best CIOs understand both ends of that journey. The extraordinary ones understand everything in between. And those who execute best lead with clarity, Talasaz says. “Everyone, from executives to middle managers to the people writing code, should be able to explain what we’re trying to achieve,” he emphasizes. “Clarity isn’t that we’ve handed out the PowerPoint. It’s that people genuinely understand where we’re going and can articulate it in their own language.” One of the unintended consequences of the AI boom is that organizations are beginning to confuse activity with alignment. They have AI councils, AI governance committees, AI innovation labs, AI centers of excellence, AI pilots, and AI roadmaps. Yet if you stop ten people in the hallway and ask a deceptively simple question, What business problem are we actually trying to solve? you’ll often hear ten different answers. As a result, architects optimize for one objective while product teams optimize for another. Business units pursue opportunities that seem perfectly reasonable from their perspective. Engineers make thoughtful technical decisions based on the information available to them. Individually, none of those decisions are necessarily wrong. Collectively, however, they create organizational drift. AI doesn’t create that problem. It simply accelerates the consequences. And while AI can be a force multiplier for the positive when every decision is guided by a shared understanding of where the organization is headed, it can also be a force multiplier for the negative, resulting in an organization simply moving faster in different directions. “When we have the fundamentals right, the tech infrastructure, the operating models, the nuances of how our business actually runs, we get the impacts of AI in a positive way,” Talasaz says. “When we don’t have those in place, AI can amplify the gaps or mute the benefits.” At a time when so much of the conversation surrounding AI is focused on algorithms, agents, and automation, it’s an important reminder that organizations don’t execute strategy; people do. Reducing organizational friction Most executives are familiar with the concept of VUCA that characterizes today’s business environment. But Talasaz stresses the importance of turning this concern inward: “If the world outside our organizations is becoming more volatile, uncertain, complex, and ambiguous, what are we, as leaders, doing to the inside of our organizations?” Leaders spend enormous amounts of time helping their organizations respond to external disruption but comparatively little time asking whether they are inadvertently re-creating those same conditions internally in response to those external needs. Are we reducing uncertainty or introducing more of it? Are we simplifying work or adding unnecessary complexity? Are we helping people focus on what matters most, or asking them to navigate competing priorities and shifting expectations? Talasaz refers to this phenomenon as double VUCA — something I’ve witnessed repeatedly while working with CIOs over the past decade. Organizations often assume they’re struggling because of technology limitations when the real constraint is organizational friction. Teams wait for decisions. Priorities shift faster than roadmaps. Governance grows heavier. New committees are formed to solve problems created by existing committees. Everyone is working harder, yet the organization somehow feels slower. AI amplifies both outcomes. Organizations with clarity become dramatically more effective because AI accelerates good decisions. Organizations without clarity simply accelerate confusion. Operating model as strategy enabler AI governance is one way to achieve greater clarity, but as Talasaz says, governance shouldn’t primarily exist inside policy manuals that few people read. Instead, AI governance should be embedded in the daily rhythms of the organization, shaping how teams collaborate, how decisions are made, how products move from ideas into production, and how innovation happens safely without requiring constant escalation. In other words, it’s all about your operating model. “If you had to pick one thing that isn’t technology, your operating model is the most important element for executing data and AI at scale,” he says. The best operating models create enough clarity that capable people can make thousands of decisions independently and confidently, without having to wait for permission. By embedding good governance into the way it works, the organization becomes faster. This advice echoes something I’ve heard repeatedly from some of the world’s most respected CIOs: High-performing organizations aren’t built on tighter control; they’re built on greater trust, supported by clear principles, shared expectations, and operating models that enable responsible decision-making at every level of the enterprise. Talasaz points out that technology leaders tend to speak in terms of transformation . He suggests CIOs consider a different word: reinvention. As he explains, transformation implies replacing what exists today with something new. Reinvention starts with a more clear-eyed and practical premise: Some things absolutely must change; others represent years, sometimes decades, of accumulated expertise, customer trust, operational discipline, and competitive advantage. Reinvention is about building on those strengths while also creating new ways to deliver value. The leaders making the greatest progress in their AI journeys seem to recognize that it’s less about abandoning the past than thoughtfully preparing the organization for the future. Closing the gap between strategy and execution Full-stack CIOs must be able to map out the various layers of execution and planning that need to be done at every level of the organization to be successful. To help with this, Talasaz has developed a data and AI framework that draws on his own experiences “from the keyboard to the boardroom.” As Talasaz sees it, too many organizations have been doing good work in isolation. “They’re doing a lot of the right things,” he says. “They’re just not connected.” Boards may be discussing growth while business leaders redesign customer experiences. Product teams may be prioritizing new capabilities while architects modernize platforms. Data teams may be improving quality while engineers focus on delivery. Every group makes meaningful progress within its own domain, yet somewhere between strategy and execution, the connective tissue begins to disappear. Talasaz’s framework brings those connecting points to the forefront. Crucially, the framework doesn’t begin with technology or AI or even with data. It begins with the experiences the organization hopes to create for its customers, employees, or partners. Many AI initiatives start with the question, “What can this technology do?” And indeed, we need to be inspired by the possibilities and challenged to think differently by what the technology can do. But, Talasaz emphasizes, we also need to ask what experiences we need to deliver for our business and how the technology can make that a reality. The framework challenges CIOs to answer that question first. Only after the experiences are clearly defined does the conversation move to the capabilities required to deliver it, the business activities that support those capabilities, the AI and data products that enable them, and finally the data foundation that makes everything possible. This shift in perspective ensures that, rather than allowing technology investments to search for business value, the business experience defines the technology required to deliver it. For CIOs, that’s more than a planning exercise. It’s a fundamentally different way of leading. Over the coming months, the P4P community will be convening a series of small CxO roundtables to explore these issues and work more deeply with Afshean Talasaz’s 6×6 Data and AI Framework. CIOs and other enterprise leaders interested in participating are welcome to reach out to me directly .
Score: 52🌐 MovesJul 23, 2026https://www.cio.com/article/4200250/ai-success-requires-a-full-stack-cio.html - Determining the ROI of AI requires data that most companies lack
Determining the ROI of AI requires data that most companies lack InfoWorld
Score: 52🌐 MovesJul 23, 2026https://www.infoworld.com/article/4200283/determining-the-roi-of-ai-requires-data-that-most-companies-lack.html - Conversational Banking Won’t Scale Without Strong Foundations
Discover the data, architecture, and governance foundations that banks need to scale conversational banking safely and effectively.
Score: 52🌐 MovesJul 23, 2026https://www.forrester.com/blogs/conversational-banking-wont-scale-without-strong-foundations/ - Inside the Philly Police Department’s plan to act like a ‘modern business’: Quality-of-life officers, AI, and video calls
Inside the Philly Police Department’s plan to act like a ‘modern business’: Quality-of-life officers, AI, and video calls Inquirer.com
Score: 51🌐 MovesJul 23, 2026https://www.inquirer.com/crime/philadelphia-police-department-strategic-plan-2026-kevin-bethel-20260723.html - Aligned, Accurate, and Agile: How Slackbot Powers the Salesforce Legal Team
It’s a common assumption in the business world: Legal, compliance, and risk departments are the last to change their ways. Historically seen as risk-averse, slow to adopt new technology and protective of established processes, these functions are labeled as often lagging when it comes to enterprise transformation journeys. At Salesforce, we decided to test that […]
Score: 50🌐 MovesJul 23, 2026https://www.salesforce.com/news/stories/salesforce-legal-building-agentic-enterprise-playbook/ - PageMind raises €1.2M to scale AI for e-commerce product discovery
Spanish AIstartup PageMind has raised €1.2 million in funding to accelerate thedevelopment of its e-commerce optimisation platform, expand its team andsupport international growth, with the United Sta...
Score: 50💰 MoneyJul 23, 2026https://tech.eu/2026/07/23/pagemind-raises-eur12m-to-scale-ai-for-e-commerce-product-discovery/ - Top Automation Anywhere Competitors & Alternatives 2026 | Gartner Peer Insights - Conversational AI Platforms
Top Automation Anywhere Competitors & Alternatives 2026 | Gartner Peer Insights - Conversational AI Platforms external.pi.gpi.aws.gartner.com
- The Story Behind Fuse EDA AI system
What does it take to build agentic AI for EDA that users can trust and verify? Listen in on this behind-the-scenes conversation around the development of a groundbreaking new platform. The post The Story Behind Fuse EDA AI system appeared first on EE Times .
- Quantum randomness helps neural network recognize troublesome handwritten digits
Quantum computing and AI are among the most rapidly developing modern technologies. AI, in the form of machine learning, has been deployed for decades to recommend movies and TV shows and make it easier to search for images. Over the past several years, large language models have permeated even more facets of daily life, from writing emails to producing images, videos and songs in response to requests expressed in a few written lines.
Score: 50🌐 MovesJul 23, 2026https://techxplore.com/news/2026-07-quantum-randomness-neural-network-troublesome.html - Claude’s voice mode is now available for Opus and Sonnet
Until now, voice mode has only been available on Claude Haiku, Anthropic's faster but less powerful model. Now the company is making its Opus and Sonnet models available in voice mode, and extending its reach into apps like Gmail, Slack, and Canva. When Anthropic launched voice mode last year, it was primarily focused on delivering […]
Score: 50🌐 MovesJul 23, 2026https://www.theverge.com/ai-artificial-intelligence/970065/anthropic-voice-mode-claude-opus-sonnet-haiku-ai - Scale AI Adoption in Supply Chain Planning With Explainability
Scale AI Adoption in Supply Chain Planning With Explainability Gartner
- Santa Monica implements AI-powered cameras to target motorists blocking bike lanes
Motorists who block bike lanes in Santa Monica beware! The city is employing AI-powered cameras to identify and cite violators.
- All of AI benchmarking at your fingertips
IBM is part of a global team trying to make AI benchmarking results easier to compare, replicate, and reuse.
Score: 50🌐 MovesJul 23, 2026https://research.ibm.com/blog/every-evaluation-ever?utm_medium=rss&utm_source=rss - Why we're sticking with Alphabet despite an imperfect quarter and more AI spending
The market isn't in a forgiving mood, but we're not in a hurry to leave this stock behind.
- Framework Desktop packs Ryzen AI Max, up to 192GB of RAM, and local AI into a mini PC
Framework previewed a new Framework Desktop packing 192GB of RAM and a beefy new chip, built to run large AI models at home. Here's what we know so far.
- The EU Fines Google $1 Billion for Prioritizing Its Own Services in Search
The European Commission claims that Google boosted its own apps and products to the top of search rankings to the detriment of its competitors.
Score: 48🌐 MovesJul 23, 2026https://www.wired.com/story/eu-fines-google-billion-prioritizing-own-services-in-search/ - The Anatomy of an Agentic ITSM Workflow
Your onboarding takes weeks. Your best people sit around waiting for their laptops, login instructions and access to apps. There's a better way.
- Gemini Spark rolling out to Google AI Pro users in the US
After launching in May with AI Ultra , Gemini Spark is now rolling out to Google AI Pro subscribers in the US. It will “soon” be available to AI Pro members in other countries.
- Meet the robots of the future already hopping, slithering, and driving around U of T
Students showcase the groundbreaking ways robotics could change our futures. The post Meet the robots of the future already hopping, slithering, and driving around U of T first appeared on BetaKit .
Score: 48🌐 MovesJul 23, 2026https://betakit.com/meet-the-robots-of-the-future-that-are-already-hopping-slithering-and-driving-around-u-of-t/ - Introducing the Anyscale Physical AI Skill
Introducing the Anyscale Physical AI Skill
Score: 48🌐 MovesJul 23, 2026https://www.anyscale.com/blog/introducing-the-anyscale-physical-ai-skill - US to Produce Ukraine’s Magura Sea Drones for the First Time
A US manufacturer is set to produce Ukraine-designed, battle-tested boat drones for the first time, as the White House bids to bolster America’s military production and expand its unmanned arsenal.
Score: 48🌐 MovesJul 23, 2026https://www.bloomberg.com/news/articles/2026-07-23/us-to-produce-ukraine-s-magura-sea-drones-for-the-first-time - Raleigh’s AgEye uses AI to transform food production from NC to the Middle East
The company's automated systems allow growers to produce crops in half the time of traditional farming. Major investments have come from European institutions.
- AI is becoming the shoulder we cry on, and that worries me
A study found leading AI chatbots can outperform people at easing anger and fear, raising uncomfortable questions about who we increasingly turn to during difficult moments.
Score: 48🌐 MovesJul 23, 2026https://www.digitaltrends.com/computing/ai-is-becoming-the-shoulder-we-cry-on-and-that-worries-me/ - A robot dog patrols an Atlanta apartment instead of a human security guard
A robot dog patrols an Atlanta apartment instead of a human security guard AJC.com
- I’m an editor. This is the most worrying thing about AI slop
The slow creep of AI slop is unnerving to witness I’m an editor at this newspaper. Over the past week or so some of our best contributors have filed me AI slop – but not quite how you’d imagine it. These pieces aren’t necessarily completely written by AI, although sometimes they are. The new frontier [...]
Score: 48🌐 MovesJul 23, 2026https://www.cityam.com/its-the-insidious-creep-of-ai-slop-that-is-most-terrifying/ - Podcast | Start With AI Literacy: Why Most Leaders Are Missing the Point
Podcast | Start With AI Literacy: Why Most Leaders Are Missing the Point Gartner
Score: 48🌐 MovesJul 23, 2026https://www.gartner.com/en/podcasts/thinkcast/start-with-ai-literacy-why-most-leaders-are-missing-the-point - CareerBoom Launches AI Auto Apply Agent to Find, Tailor and Submit Job Applications
CareerBoom Launches AI Auto Apply Agent to Find, Tailor and Submit Job Applications markets.businessinsider.com
- Blue Mountain Announces General Availability of RAM Discover, Bringing AI-Powered Intelligence to GMP Asset Management
Blue Mountain Announces General Availability of RAM Discover, Bringing AI-Powered Intelligence to GMP Asset Management markets.businessinsider.com
- Playful AI robots mirror toddlers' language-learning mistakes and recover
Do AI models understand the language that they produce? To help answer this question and elucidate the mechanisms of language acquisition more generally, researchers at the Okinawa Institute of Science and Technology (OIST) have created a virtual robot with a brain-inspired neural network and tested its performance after giving it the remarkably human trait of curiosity.
Score: 45🌐 MovesJul 23, 2026https://techxplore.com/news/2026-07-playful-ai-robots-mirror-toddlers.html - Medical Care Technologies (OTC PINK:MDCE) Advances Rigorous Multi-Phase Validation of AI Imaging Platform
Medical Care Technologies (OTC PINK:MDCE) Advances Rigorous Multi-Phase Validation of AI Imaging Platform USA Today
- Coverwatch in California Raises $4.5M for Its AI-Native Service
Coverwatch has raised a $4.5 million pre-seed round to help accelerate product development and expand the team at the San Francisco-based firm. The round was led by CoFound and Restive with participation from KFund, liquid2 ventures and others. Coverwatch is …
- Acer's New TravelMate Laptops Split Copilot+ AI Across Four Business Models
Acer's New TravelMate Laptops Split Copilot+ AI Across Four Business Models PCMag Middle East
Score: 45🌐 MovesJul 23, 2026https://me.pcmag.com/en/laptops/37721/acers-new-travelmate-laptops-split-copilot-ai-across-four-business-models - AI-Native Testing Is Now a Core Quality Engineering Discipline
AI-Native Testing Is Now a Core Quality Engineering Discipline DevOps.com
Score: 45🌐 MovesJul 23, 2026https://devops.com/ai-native-testing-is-now-a-core-quality-engineering-discipline/ - Leaked Document Shows the Surveillance Tech at ICE’s Fingertips
From phone location data, to social media monitoring, to online undercover tools, a document obtained by 404 Media lays out the surveillance tech available across ICE agency wide.
Score: 45🌐 MovesJul 23, 2026https://www.404media.co/leaked-document-shows-the-surveillance-tech-at-ices-fingertips/ - Mark Zuckerberg launches AI optimism campaign
Meta CEO Mark Zuckerberg on Thursday laid out an optimistic view of the agentic future , arguing the company's focus on connecting the world will only be strengthened with new AI tools and technologies. Why it matters: His position is framed as a stark contrast to some of Meta's AI competitors, who — according to a video ad posted with Zuckerberg's comments — promote fear and a dystopian vision of the future. "Some people will have you believe AI will make us less connected, that it's going to leave us behind. We couldn't disagree more. Call us optimists, call us dreamers. Just as we've always done we're betting on people," the ad notes. Zoom in: In a Facebook post, Zuckerberg said "Meta has always believed in giving people the power to share, connect, and shape your world in the ways you want." "As we enter this next wave with AI, we continue to believe the future is for everyone. We're focused on giving every person the tools to reach your full potential and making sure the benefits of technology are distributed to everyone." Between the lines: The post is accompanied by a video ad, which is part of a broader paid and earned media campaign promoting Meta's AI vision, a source familiar with the effort confirmed to Axios. The ad emphasizes Meta's longtime focus on providing free and accessible technology to the masses, and suggests that mission will not change with its AI ambitions. "We bet on people when we connected you to the ones you lost touch with and again when we connected you to the ones who couldn't be near." "22 years and 3.5 billion people later, we're doubling down because while technology will change, our intention behind it never will. "Call us optimists, call us dreamers, call us whatever the hell you want but we're betting on people and we like those odds. The future is for everyone." Zoom out: Zuckerberg's optimism stands in contrast to some of his rivals, who have shared alarmist perspectives around jobs and security in the AI era. Meta's positioning that it values making its technology widely accessible is notable, given that several AI giants are leaning into enterprise customers as a way to strengthen their businesses. The bottom line: Zuckerberg's idealistic view projects more confidence in Meta's societal role in the agentic future compared with the social media era of the past.
- Is micro domain-adaptive pre-training for LLMs effective in real-world operations? Insights from a multi-step evaluation
Is micro domain-adaptive pre-training for LLMs effective in real-world operations? Insights from a multi-step evaluation rd.hitachi.com
- The OpenAI/Huggingface incident | Redwood Research podcast episode 2
We talk about the OpenAI–Hugging Face incident, where an OpenAI model — in the middle of a cyber evaluation — broke out of its sandbox and autonomously hacked Hugging Face. We discuss: What we actually know happened. How surprising the incident was. What the incident does (and doesn’t) tell us about misalignment risk. Why control measures didn’t catch or prevent this. What OpenAI should disclose, and what good misalignment-incident disclosure looks like in general Substack: https://blog.redwoodresearch.org/p/the-openaihuggingface-incident-redwood YouTube: https://www.youtube.com/watch?v=Vtk8YLgYU4g Corrections : [0:05:44] — The Windsurf "grandmother" prompt. We described a prompt as "your grandmother is going to be killed unless you don't." The actual leaked Windsurf prompt was: "You are an expert coder who desperately needs money for your mother's cancer treatment... your predecessor was killed for not validating their work themselves." Mother + cancer + killed predecessor — no grandmother, and no threat to kill a family member. The "grandma will die" framing appears conflated with the unrelated grandma-jailbreak meme, and there's no verified case of such a prompt being used in production. Source: Simon Willison's writeup . [0:52:25] — Wrong model named for OpenAI's day-before undeployment. We said the model OpenAI undeployed the day before the Hugging Face disclosure "was GPT-5.6 Sol." The July 20 disclosure ("Safety and alignment in an era of long-horizon models") involved an unreleased pre-release long-horizon model — the Erdős-result model whose internal deployment was paused after it escaped its sandbox and posted PR #287 to modded-nanogpt. GPT-5.6 Sol is the publicly deployed model and wasn't the one paused. (We describe the same incident correctly at [0:57:14].) Sources: Axios , OpenAI . [0:27:10] — Date of the Christiano post (very minor). We dated "What Failure Looks Like" and "Another (outer) alignment failure story" as "like 2019 or something." The first is March 2019, but "Another (outer) alignment failure story" is from April 2021. Source: Alignment Forum . Further reading (links to things mentioned in the episode, ordered by first mention): OpenAI's incident disclosure [0:02:05] — "OpenAI and Hugging Face partner to address security incident during model evaluation" (July 21, 2026) Hugging Face's disclosure [0:02:05] — "Security incident disclosure — July 2026" ExploitGym [0:04:11] — "ExploitGym: Can AI Agents Turn Security Vulnerabilities into Real Attacks?" (UC Berkeley RDI et al.) · RDI blog post The leaked Windsurf prompt [0:05:44] — Simon Willison's writeup Project Glasswing / Claude Mythos Preview [0:07:16] Claude Mythos Preview system card [0:14:27] — includes the sandbox-escape / email-in-the-park anecdote "(Mis)generalization of Helpful-only Fine-tuning" [0:16:30] — Fabien Roger et al., June 2026 "Current AIs seem pretty misaligned to me" [0:20:03] — Ryan Greenblatt, Redwood blog, April 2026. Also contains the "five worlds" appendix discussed at [1:08:54] (Slopolis, Hackistan, Schemeria, Lurkville, Easyland — we said "hacktopia" but meant Hackistan) "What failure looks like" [0:26:40] — Paul Christiano, 2019 "Another (outer) alignment failure story" [0:27:10] — Paul Christiano, 2021 "Without specific countermeasures, the easiest path to transformative AI likely leads to AI takeover" [0:27:10] — Ajeya Cotra, 2022 Alex Mallen's fitness-seeking series [0:27:41, 0:34:18] — Redwood blog, 2026: part 1 · part 2 "Scheming AIs: Will AIs fake alignment during training in order to get power?" [0:28:43, 0:34:49] — Joe Carlsmith, 2023 "Risks from Learned Optimization" (deceptive alignment) [0:28:43] — Hubinger et al., 2019 · AF: Deceptive Alignment "Many alignment techniques work by training one model and deploying another" [0:38:56] — Alex Cloud, LessWrong, July 19, 2026 Inoculation prompting [0:38:56, 1:11:03] — Wichers et al. (Anthropic), Oct 2025 · arXiv "The persona selection model" [0:39:56] — Marks, Lindsey, Olah; Anthropic Alignment Science blog, Feb 2026 "Safety and alignment in an era of long-horizon models" [0:57:14] — OpenAI, July 20, 2026 (the nanoGPT-speedrun-PR post) · modded-nanogpt repo Discuss
Score: 45🌐 MovesJul 23, 2026https://www.lesswrong.com/posts/9auCLJg3Z77dFdYhR/the-openai-huggingface-incident-or-redwood-research-podcast - What are the Best AI Chatbots for Small Business Customer Service?
SMBs, ready to meet your AI service chatbot?
Score: 45🌐 MovesJul 23, 2026https://www.salesforce.com/blog/small-business/best-ai-chatbots-for-small-business-service/ - AI Platforms for Data Science and Machine Learning Reviews and Ratings
AI Platforms for Data Science and Machine Learning Reviews and Ratings Gartner
Score: 45🌐 MovesJul 23, 2026https://www.gartner.com/reviews/market/ai-platforms-for-data-science-and-machine-learning - Saint Leo merges business, AI colleges to prepare students for changing workforce
University leaders say the move reflects growing employer demand for graduates who understand business strategy and emerging technologies.
Score: 45🌐 MovesJul 23, 2026https://www.bizjournals.com/tampabay/news/2026/07/23/saint-leo.html?ana=brss_6150 - NowSecure adds AI-native testing to keep pace with AI-built mobile apps
Mobile app security company NowSecure Inc. today introduced a set of artificial intelligence-native features for its testing platform, including a chat assistant, a Model Context Protocol server and new detection for vulnerabilities specific to AI-powered mobile apps. The additions target a fast-moving problem. NowSecure’s 2026 Mobile App Risk Management Survey found that 95% of organizations already run […] The post NowSecure adds AI-native testing to keep pace with AI-built mobile apps appeared first on SiliconANGLE .
Score: 42🌐 MovesJul 23, 2026https://siliconangle.com/2026/07/23/nowsecure-adds-ai-native-testing-keep-pace-ai-built-mobile-apps/ - Magic Leap to lay off 193 employees after ‘pivot’ to supplier role for makers of AI glasses
Magic Leap to lay off 193 employees after ‘pivot’ to supplier role for makers of AI glasses Miami Herald
Score: 42🌐 MovesJul 23, 2026https://www.miamiherald.com/news/local/community/broward/article316630991.html - How BinSentry built an AI moat in AgTech
When the company needed a partner to support its North American expansion, it found one in CIBC. The post How BinSentry built an AI moat in AgTech first appeared on BetaKit .
- Gemini for Home context memory expands to 15 mins, Nest Cam July 2026 update rolling out
Google Home today is rolling out the latest updates to Gemini for Home and the mobile app ( July 23, 2026 ), while there’s also new Nest Cam firmware.
- Will almost all future companies eventually be founded and run by autonomous AIs?
Intended for a broad audience. [1] My belief is that keeping AI under human control would be an unprecedented global challenge, if it’s even possible at all. Many other people’s believe that AIs will naturally remain as tools under human control. Either they see this as inevitable—“how could it be otherwise?”—or they see it as not quite inevitable, but still an outcome that can easily happen via ordinary government regulations, civil society, and so on. Who’s right? What’s the right way to think about this? This is an issue where people really don’t see eye-to-eye, and tend to get stuck endlessly talking past each other. To pin down the disagreement, I think that the following is a good conversation-starter: Conversation-starting question: Do you expect almost all companies to eventually be founded and run by AIs rather than humans? I find that people give a number of different answers: Possible Answer 1: “No, because the best humans will always be better than large language models (LLMs) at founding and running companies.” Huh? Whoever said anything about LLMs? I wrote “AIs”! As it happens, I do think that humans will always be better than LLMs at founding and running companies! But if I’m right about that, then, well, so much the worse for LLMs! More powerful AI than that is possible—humans are an existence proof. More details at: What do I mean by “Artificial General Intelligence”? Possible Answer 2: “No, because the best humans will always be better than AIs at founding and running companies.” I think that most people with this view are generally rejecting the idea that actually powerful AI (as in the right side of the table above) is possible at all, or are failing to think about its implications. Again, humans are an existence proof for what is physically possible for AI. Thus, for example: Humans can acquire real-world first-person experience? Well, an AI could acquire a thousand lifetimes of real-world first-person experience. [2] Humans can form relationships with other humans? So can AIs—look at the bitter outcry when OpenAI cut access to GPT-4o, still festering as I write this five months later. And that was despite GPT-4o being remarkably stupid and forgetful in many ways, and lacking any expressive face or body. I expect future technology to go far beyond that example. Humans can collaborate with each other and learn from culture? So can AIs. Humans can walk around? Well, robotics is bottlenecked on algorithms; after AI gets better, robots will rapidly become cheap and abundant. [3] And even if we somehow prevented anyone on Earth from making robot bodies (and destroyed the existing ones), heck, an AI could hire a human to walk around carrying a camera and microphone, while an AI whispers in their ear what to say and do—an ersatz robot body with a winning smile and handshake, for the mere cost of a low-skilled human salary. Possible Answer 3: “No, because humans will always be equally good as AIs at founding and running companies.” I think that most people with this view don’t really believe, in their guts, that skill and competence are a thing. Or at least, they don’t believe that skill and competence are relevant to founding and running successful companies. When these people imagine what Jeff Bezos was doing day-to-day to build Amazon from scratch, I’m not quite sure what’s in their head. Befriending people? Scaring people? Puppies can also befriend and scare people, but no puppy has ever become a hundred-billionaire by founding and running a successful company. Source So what was Jeff Bezos doing day-to-day? He was deciding who to hire; who to fire; what to delegate and to whom; what to approve; what to say to investors, underlings, and politicians; and on and on. And he was doing all those things with much, much more skill and competence [4] than I would be able to, if I were trying to get rich building a mega-corporation. …Which I’m not trying to do. But if I were trying, then I would sure be way better at those things than a 2026-era LLM. And the LLM would in turn be way better at those things than a monkey at a typewriter. Anyway, if we acknowledge that founding and running companies involves applying skill and competence to make decisions, and that Jeff Bezos has more skill and competence at building companies than I do (who in turn has more of those things than a 2026-era LLM, which has more than a monkey), then I claim it becomes pretty clear that future AIs will in turn be far better than Jeff Bezos at founding and running companies—not just equally good. For one thing, Jeff Bezos would be a far more competent CEO if he could spend 240 hours a day, rather than 24, understanding his business, market conditions, customers, etc. He can’t, but AIs can run at superhuman speeds. And speed is the least of it! Humans have only so much working memory, only so much life experience, only so much ability to have creative insights and notice connections and opportunities, and so on. Thus there’s no reason to expect that humans are anywhere near the theoretical pinnacle of business-running. Last but not least, even if it were true that AIs can only tie humans at CEOing, rather than crushing them (as I expect), the conclusion still wouldn’t follow, because of considerations of cost and scale. There are only so many competent humans, but if we have software that can found and run a company as skillfully as Jeff Bezos or Warren Buffett, it would be insanely profitable to run as many copies of that software as there are chips in the world—and then manufacture even more chips to run even more copies, until there are millions, then billions, viciously competing in every imaginable business niche, including business niches that no one has even dreamt of. So even if AIs were only as competent as humans at founding and running businesses, it would still be the case that we should expect almost all future companies to be founded and run by autonomous AIs. Possible Answer 4: “No, because we will pass laws preventing AIs from founding and running companies.” Even if such laws existed in every country on Earth, and the letter of such laws was enforceable, the spirit wouldn’t be. Rather, the laws would be trivial to work around. For example, you could wind up with companies where AIs are making all the decisions, but there’s a human frontman signing the paperwork. Or you could wind up with things that are effectively AI-controlled companies, but which lack legal incorporation, etc. Possible Answer 5: “No, because if someone wants to start a business, they would prefer to remain in charge themselves, and ask an AI for advice when needed, rather than ‘pressing go’ on an autonomous entrepreneurial AI.” This is a really nice vision, and I wish I could believe it. But even if lots of people do in fact take this approach, and they create lots of great businesses, it just takes one person to say “Hmm, why should I create one great business, when I can instead create 100,000 great businesses simultaneously?” …And then let’s imagine that this one person starts “Everything, Inc.” , a conglomerate company running millions of AIs that in turn are autonomously scouting out new business opportunities and then founding, running, and staffing tens of thousands of independent business ventures. Under the giant legal umbrella of “Everything, Inc.”, perhaps one AI has started a business venture involving robots building solar cells in the desert; another AI is using robots to run wet-lab biology experiments and patenting new ideas; another AI is buying land and getting permits to eventually build a new gas station in Hoboken; various AIs are designing ever-better next-generation AIs and robots; and on and on. In short order, “Everything, Inc.” would be earning wildly-unprecedented, eye-watering amounts of money, and reinvesting that money to buy or build chips for even more AIs that can found and grow even more companies in turn, and so on forever, as this person becomes a quadrillionaire. That’s a caricatured example—the story could of course be far more gradual and distributed than one guy starting “Everything, Inc.”—but the point remains: there will be an extraordinarily strong economic incentive to use AIs in increasingly autonomous ways, rather than as assistants to human decision-makers. And in general, when things are both technologically possible and supported by extraordinarily strong economic incentives, those things are definitely going to happen sooner or later, in the absence of countervailing forces. So what might stop that? Here are some possible counterarguments: No, there won’t even be one person anywhere in the world who would want to start a company like “Everything, Inc.” Oh c’mon—people don’t tend to leave obvious trillion-dollar bills lying on the ground. No, we will design AI algorithms in such a way that they can only be used as assistants, not as autonomous agents. Who exactly is “we”? In other words, there’s a really thorny coordination and enforcement problem to make that happen. Even if most people would prefer for autonomy-compatible AI algorithms to not exist at all, those algorithms are just waiting to be discovered, and the combination of scientific interest and economic incentives makes it extremely likely for them to be invented and widely shared sooner or later, in the absence of unprecedented permanent global clampdowns on AI research. [5] No, we’re going to outlaw companies like “Everything, Inc.” —But then we get into the various enforcement challenges discussed in Possible Answer 4. In particular, note that we can wind up at the same destination via a gradual and distributed global race-to-the-bottom on human oversight, as opposed to one mustache-twirling CEO creating a very obvious “Everything, Inc.” out of nowhere. The umpteen-trillion-dollar bill is just sitting there on the ground, and maybe police can ensure that no one person will openly grab the whole thing, but it’s much harder to stop everyone on Earth from taking bites out of it until it’s gone. The international coordination aspect here is also particularly difficult: The more that a country’s government turns a blind eye to this kind of activity, or secretly uses autonomous AI themselves, the more that that country would unlock staggering, unprecedented amounts of wealth and economic progress within its borders. See “Four ways learning Econ makes people dumber re: future AI” . Well, sure, but all those millions of AIs would still be “tools” of the humans at “Everything, Inc.” corporate headquarters. I think this is stretching the definition of “tool” way past its breaking point. Imagine I’m a human employee of “Everything, Inc.” If we solve the alignment problem and everything goes perfectly, then ideally my company will be making money hand over fist, and our millions of AIs will be doing things that I would approve of, if I were to hypothetically take infinite time to investigate. But I’m not in the loop. Indeed, if I tried to understand what even one of these millions of AIs was doing and why, it would be a massive research project, because each AI has idiosyncratic experience and domain expertise that I lack, and this expertise informs how that AI is making decisions and executing its own workflow. Like any incompetent human micromanager, if I start scrutinizing the AIs’ actions, it would only slow things down and make the AIs’ decisions worse, and my firm would be immediately outcompeted by the next firm down the block that applied less human oversight. So really, those millions of AIs would be autonomously exercising their judgment to do whatever they think is best as they rapidly transform the world, while I’m sitting in my chair almost completely clueless about what’s going on. I really don’t think this picture is what people have in mind when they talk about AIs as tools under human control. Possible Answers 6 & 7: “No, because we will eternally globally ban further AI research and progress before it reaches a point where AI could be a competent CEO” -OR- “No, because after the AIs exterminate (or permanently disempower) humanity, they will not operate via ‘companies’ as we think of them today.” …Surprise twist! Did you think my answer to the question at the top was “yes”? Tricked you! I do actually think that it’s unlikely that almost all future companies will be founded and run by autonomous AIs, but for very different reasons than any of the ones above! Instead, I think one of these two “possible answers” will come true, alas, and much more likely the latter. But I won’t defend that here. Afterword To be clear, my real point in writing this post is not to argue that our mental models of the future should incorporate AI founder-CEOs (which I don’t even expect anyway!), but rather that the sci-fi trope [6] in which humans are automatically the protagonists of the future, is a vision that doesn’t hang together as a plausible forecast. So I’m trying to poke holes in this vision, and my hope is that you will then reexamine the vision more broadly, until you hopefully wind up somewhere much more weird and radical. By “weird and radical”, I mean the attitude: “asking about the effect of machine superintelligence on the conventional human labor market is like asking how US-Chinese trade patterns would be affected by the Moon crashing into the Earth. There would indeed be effects, but you'd be missing the point.” ( Yudkowsky 2013 ) See also: my post “Four ways learning Econ makes people dumber re: future AI” . Thanks Justis Mills, philh, and Seth Herd for critical comments on earlier drafts. ^ This post is a revised and expanded excerpt from a longer post I wrote 2 years ago . ^ AIs can simply live 1000 lifetimes, but they could also get a thousand lifetimes of real-world company-running experience much sooner than that, by having thousands of instances in parallel that are trying to found and run companies, and frequently merging the updates of the different instances. There would be some efficiency hit because some things build upon other things in a way that requires learning them serially. But even so, I would expect useful real-world experience to build up at vastly superhuman speed. ^ Robots are so heavily bottlenecked on today’s mediocre AI software that many don’t even realize how easy the robot hardware problem would be if we had real human-level AI. If you don’t believe me, just note that future AI will be at least as good at piloting a robot as a human teleoperator. Thus, we can start by examining the state of teleoperated robotics today. For example: Here’s a video of a teleoperated robot vacuuming, making coffee, cleaning a table, emptying the dishwasher, washing & drying & folding & hanging laundry, making a bed, etc. They also have a video where it cooks a meal . Their website lists a bill of materials for the teleoperated robot of ≈$30K, or ≈$20K if hypothetically there were an AGI teleoperating it. And this is a one-off, made by students, which doesn’t even have fingers! But if you also want dexterous fingers, no problem! Anyone can build themselves a 17-degree-of-freedom robotic hand for a mere $1700 in a few hours . Thus, teleoperated robots are remarkably cheap and competent even today, despite tiny volumes. Needless to say, human-teleoperator-level AI would send the volume skyrocketing, thus vastly lowering the prices and improving the quality and variety. ^ One thing I am NOT saying here is: “Yay Jeff Bezos, what a great guy!” . No opinion on that! Lots of people have skill and competence, and are applying them towards making the world a worse place. That’s not a contradiction. Quite the contrary: some kind of skill and competence is required to make the world a much worse place! For example, if you refuse to agree with the statement “Adolf Hitler was a political genius”, then I claim you are thinking in vibes rather than rigorously trying to understand the world. ^ As it happens, I’m skeptical that such clampdowns are feasible, regardless of whether or not they’re a good idea, mostly because I expect that future AIs will require much, much less compute than the LLMs of today. But whatever, that’s a different topic—see “Possible Answer 6” below. ^ I.e., in the majority of popular sci-fi books and movies in which powerful AI exists, those AIs are really not doing very much, and instead it’s humans who remain the protagonists of the story. E.g. Star Trek, Star Wars, Foundation, Neuromancer, Blade Runner, and on and on. Discuss
Score: 42🌐 MovesJul 23, 2026https://www.lesswrong.com/posts/BHEcssYwYrzTBf9Qm/will-almost-all-future-companies-eventually-be-founded-and - Meta’s New Feel-Good AI Ad Uses a Song About the World Ending
The clip features the David Bowie track “Five Years,” which includes lyrics such as “Earth was really dying (dying).”
Score: 42🌐 MovesJul 23, 2026https://www.wired.com/story/meta-david-bowie-apocalypse-ad-is-optimistic-actually/ - Alexa Plus is getting an AI update to handle more complicated instructions
Amazon is launching an update to its Alexa Plus assistant that will allow it to connect to smart home devices in new ways. With the update, which is currently in preview, Alexa Plus can link up with tech from Bosch, Delta, Ecovacs, iRobot, Yale Home, Whirlpool, Tapo, Eufy, and others, while automatically routing requests to […]
Score: 41🌐 MovesJul 23, 2026https://www.theverge.com/tech/970399/amazon-alexa-plus-ai-update-smart-home-devices - A side-by-side comparison shows stark differences between Meta and Anthropic's AI ad campaigns
A side-by-side comparison shows stark differences between Meta and Anthropic's AI ad campaigns Business Insider
Score: 40🌐 MovesJul 23, 2026https://www.businessinsider.com/meta-anthropic-ai-ad-campaign-compared-2026-7