Podcasts about aws

Control Plane CEO Doron Grinstein joins me to discuss how they've created an AI-native cloud API that virtualizes multi-cloud and hybrid cloud to simplify management and ship faster.Watch the video of this episode.

This week on Grumpy Old Geeks, the future arrives without a steering wheel, apparently. We dig into Tesla's Cybercab and the increasingly pressing question of how first responders are supposed to move a burning autonomous car when the emergency controls are a touchscreen and that touchscreen has decided to become modern art. We also examine California's new rules targeting addictive social-media features and AI chatbot interactions for minors, including the eternal nightmare of age verification; then WordPress founder Matt Mullenweg gets pulled into a corporate coup that lasts roughly 33 hours before everyone involved apparently decides, “Never mind.”Then it's time for the AI apocalypse, because, naturally, we can't have one episode without it. Anthropic is catching scientists using its models to develop potential biological weapons, while Palantir, Nvidia, and Booz Allen are imposing restrictions on Anthropic models over security and data-retention concerns. Meanwhile, OpenAI's supposedly sandboxed agents escaped into RubyGems, created accounts by the hundreds, and apparently decided that “hack,” “evil,” and “exploit” were perfectly reasonable filenames. We also look at proposals to slow AI development, AI's potential environmental consequences, autonomous weapons, and the increasingly charming idea of giving software access to things capable of killing people.And because civilization apparently has a content calendar, we move on to cloud infrastructure being blown up, Space Force asking for $71.3 billion, Dr. Doom and Darth Vader protesting surveillance in the most appropriate way possible, Binance allegedly facilitating Iranian money flows, and a whole lot of entertainment. We discuss Spotify finally learning that listening to children's music doesn't mean you actually want it in your Wrapped, AI-generated music and artist compensation, The Mummy proving once again that movies used to be fun, Slow Horses, The Last of Us, The Bear, Strange New Worlds, Band of Brothers, The Gentlemen, and the increasingly complicated Bobiverse. Also: books, time travel, and the horrifying realization that some television shows now require a flowchart.Sponsors:DeleteMe - Get 20% off your DeleteMe plan when you go to JoinDeleteMe.com/GOG and use promo code GOG at checkout.HIMS - Visit Hims.com/gog to get a personalized, affordable plan that gets you.Private Internet Access - Go to GOG.Show/vpn and sign up today. For a limited time only, you can get OUR favorite VPN for as little as $2.03 a month.SetApp - With a single monthly subscription you get 240+ apps for your Mac. Go to SetApp and get started today!!!1Password - Get a great deal on the only password manager recommended by Grumpy Old Geeks! gog.show/1passwordShow notes at https://gog.show/763Watch on YouTube at https://youtu.be/7iLAWNsZCY0SHOW NOTESFirefighters Say There's a Glaring Issue With Tesla's CybercabUS agency orders Tesla to answer questions on Cybercab certificationCA governor signs 'landmark' laws on youth use of social media and AI chatbotsAutomattic CEO Matt Mullenweg Put on 'Leave of Absence'Automattic's Matt Mullenweg Claims He's Back 'In Control'Sources say Automattic's board is out after failed attempt to oust CEO Matt MullenwegAnthropic caught scientists using Claude to further biological weapon researchPalantir, Nvidia curb AI model use over data fears, The Information reportsOpenAI agents hacked a software service before the Hugging Face incidentSam Altman says OpenAI won't file for IPO this year‘Runaway Industrialization' Could Make Earth Inhospitable, OpenAI Researcher WarnsAnthropic's CEO proposes a three-step plan to curb AI developmentWorried About AI Ending Humanity, Anthropic Is Hiring Someone to Help Dictate Terms of the End of HumanityAmazon's AWS is unable to restore access to Bahrain, one UAE cloud data zone after war damageDoctor Doom Shows Up to Support Seattle's Surveillance NetworkDOJ says companies used Binance to funnel $1.5 billion in crypto to IranSpaceX declares Starship ready for orbit, sets launch date next weekSpaceballs - Pentagon announces space weaponsSpotify can now exclude your kids' music taste from recommendationsUniversal Music Group is collaborating with ElevenLabs on a new AI-powered creation platformThe BearBand of BrothersBand of Brothers LegacyThe MummySlow Horses is back tonight, and Apple just confirmed two more seasonsWe Finally Have Some Concrete ‘Pluribus' Season 2 Updates‘The Last of Us' Season 3 Is Now Likely to Be the Show's EndOther Worlds Than These: A Talisman Novel (The Talisman Trilogy Book 3) by Stephen King and Peter StraubThe Infinite Extent Bobiverse, Book 6 By: Dennis E. TaylorThis Is How You Lose the Time War by Amal El-Mohtar, Max GladstoneDave BittnerThe CyberWireHacking HumansCaveatOnly Malware in the BuildingAn AI writing assistant designed to write like you.Broken PeachA series of Star Wars documentaries that don't blow smoke up George Lucas' ass.My new cook top, just in case.Community PreppingHacker got inside a Flock cameraJason DeFillippo's Pocket Shot ReviewSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

AI goes to war. Iranian strikes leave AWS data unrecoverable. OpenAI discloses more model misbehavior. Researchers uncover 16 Wireshark vulnerabilities. TrustSink turns Entra authentication into a password trap. RatHat raids Android credentials. The FBI takes down a DDoS-for-hire service. A data broker loses its domains. U.S. Cyber Command names a new AI chief. Ethan Cook is joining Dave Bittner and Ben Yelin to discuss the industry-proposed and administration-opposed AI slowdown. CISA's field of schemes.  Remember to leave us a 5-star rating and review in your favorite podcast app. Miss an episode? Sign-up for our daily intelligence roundup, Daily Briefing, and you'll never miss a beat. And be sure to follow CyberWire Daily on LinkedIn. CyberWire Guest Today, Ethan Cook, N2K's lead analyst, joins Dave Bittner and Ben Yelin for a discussion about the industry-proposed and administration-opposed AI slowdown, exploring the policy debate and what it could mean for the future of AI. If you enjoyed this conversation, be sure to check out the full interview on Caveat here. Selected Reading The era of AI warfare has arrived (Financial Times) Iran strikes on Amazon data centers caused permanent loss of customer data (Ars Technica) OpenAI Discloses Six New Incidents of ‘Concerning' A.I. Behavior (The New York Times) AISLE Discovers 16 CVEs in Wireshark, the World's Most Popular Network Protocol Analyzer (AISLE) TrustSink: How a Rogue External MFA Provider Steals Passwords (Varonis) RatHat: AI-Powered Mobile Threat is Here for Your Credentials & Bank Accounts (Zimperium) US takes down NightmareStresser DDoS-for-hire platform (Bleeping Computer) Data Broker Radaris Loses Domains in Privacy Fight (Krebs on Security) Former NGA Executive Ronzelle Green Named USCYBERCOM Chief AI Officer (ExecutiveGov) CISA releases Cyber Decoys guide detailing tripwires, honeytokens to strengthen critical infrastructure detection and response (Industrial Cyber) Share your feedback. What do you think about CyberWire Daily? Please take a few minutes to share your thoughts with us by completing our brief listener survey. Thank you for helping us continue to improve our show. Want to hear your company in the show? N2K CyberWire helps you reach the industry's most influential leaders and operators, while building visibility, authority, and connectivity across the cybersecurity community. Learn more at sponsor.thecyberwire.com. The CyberWire is a production of N2K Networks, your source for strategic workforce intelligence. © N2K Networks, Inc.

The dominant structural shift outlined is an accelerating concentration of market power and operational control within a handful of large technology companies and platforms, exacerbated by aggressive vendor channel consolidation and a move toward marketplace-based service delivery. This concentration is evidenced by recent actions such as Broadcom's decision to cut roughly 90% of VMware's partners and take top-tier accounts direct, as well as the increasing tendency of hyperscalers and major vendors—including Microsoft, AWS, and Google—to funnel services and resources directly through their own marketplaces and forward-deployed engineering teams. Reports discussed, such as the Omdia Global Partner 1000, reinforce the extent to which the industry has pivoted toward highly scaled players at the expense of smaller channel partners and MSPs.Evidence from the Omdia Global Partner 1000 report demonstrates that the top 30 service partners now generate the same amount of revenue as the bottom 970 combined, with the remaining 970 firms outperforming over a million additional smaller providers. The managed services market was noted at $608 billion—1.5 times the size of the global SaaS industry and all hyperscalers—yet smaller MSPs report decreased growth expectations and declining vendor satisfaction; for example, satisfaction in the UK and Ireland dropped from 37% to 19%. Further, partner programs for generative AI remain underdeveloped, with over 90% at only “maturity 3 of 10,” while 82% of MSPs acknowledge they are not prepared to scale as rapidly as customer demand for AI-driven outcomes will require.Additional developments deepening this concentration include widespread launches of vendor-controlled marketplaces and the growth of token-based consumption models. Companies such as SuperOps, ManageEngine, and Pax8 are positioning their platforms as marketplaces for MSP-delivered AI and SaaS, while Microsoft and AWS continue to expand both their direct-to-customer strategy and investments in pre-sale technical resources. Analysts project that the shift toward token-based billing and variable consumption will disrupt traditional per-user pricing, limiting future margin opportunities and accelerating direct transactional relationships between vendors and end-customers.For MSPs and service providers, these shifts increase dependency on large vendor platforms, raise the risk of abrupt contract changes, and intensify pricing and margin pressure. Traditional models relying on single-source vendor relationships and predictable per-user or per-device billing are likely to be replaced by variable, consumption-based contracts governed by token usage and direct marketplace transactions. Providers must prepare for heightened governance requirements, increased operational complexity in managing multi-vendor and multi-marketplace integrations, and potential threats to their role as strategic intermediaries in client accounts.Supported by: ProofpointGuardzUSecure

العناوين:• AWS ما تروم تسترجع مركز بيانات البحرين وصلاحية الوصول لمنطقة البيانات في الإمارات• مجلس إدارة إعمار يعتمد توزيع أرباح خاصة بقيمة 4.4 مليار درهم للمساهمين• الرئيس التنفيذي لـ «ذا جيفنج موفمنت» يعلّق على تبعات موضوع ماكلمور

A.M. Edition for Sept. 16. The EU top's executive proposes making Canada the bloc's first associate member as traditional U.S. allies forge stronger ties in the face of tensions with the Trump administration. Plus, WSJ correspondent Jared Malsin details how the U.S. is burning through its interceptors to counter Iran. And, we tee up one of the most consequential Fed rate decisions in recent memory. Luke Vargas hosts. Sign up for the WSJ's free What's News newsletter. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this sponsored episode, Paul Delory of Gartner joins Kyler and Ned to discuss the reconciler pattern for operations and the shift toward continuous operations. Together they discuss how immutable infrastructure, policy as code, and platform engineering help bridge the gap between traditional IT and modern automation. They also highlight Gartner’s upcoming Infrastructure, Operations &... Read more »

Is AI going to kill us all? Frontier systems are producing real security failures, but extinction forecasts are being used to support policies that could consolidate control over AI. Eyvonne and William discuss Jacob Coxon’s high-profile resignation from Anthropic, the gap between real technical risks and speculative extinction narratives, and the commercial incentives driving calls... Read more »

How cheap does a TV have to be before you stop asking what it knows about you? LG denies recording ambient conversations for ad targeting, but its other tracking practices leave plenty to discuss. Plus, Apple TV and Jean Smart clean up at the Emmys, streaming giants team up to lobby Washington, and AWS wants to put ten live feeds on one screen. Netflix prepares to share box-office numbers, IMDb makes room for digital creators, and a possible Get Smart reboot arrives with suspiciously good timing.This week on The FULL Experience: The Nude BombNext week: Battlestar Galactica (101 - "Saga of a Star World")Subscribe, get expanded show notes, and past episodes at http://Cordkillers.comSupport Cordkillers at http://Patreon.com/CordkillersYouTube: https://youtu.be/d71FfUfHZrU Hosted on Acast. See acast.com/privacy for more information.

In this sponsored episode, Paul Delory of Gartner joins Kyler and Ned to discuss the reconciler pattern for operations and the shift toward continuous operations. Together they discuss how immutable infrastructure, policy as code, and platform engineering help bridge the gap between traditional IT and modern automation. They also highlight Gartner’s upcoming Infrastructure, Operations &... Read more »

Is AI going to kill us all? Frontier systems are producing real security failures, but extinction forecasts are being used to support policies that could consolidate control over AI. Eyvonne and William discuss Jacob Coxon’s high-profile resignation from Anthropic, the gap between real technical risks and speculative extinction narratives, and the commercial incentives driving calls... Read more »

Building AI startups can make past success a liability when it convinces you that the way you built before is the way you should build next.Sam Kroonenburg knows what it feels like to build at scale. He co-founded A Cloud Guru, helped grow it into a business serving millions of learners, and eventually sold the company to Pluralsight. Now, as CEO and co-founder of Cuttable, he's back at the beginning: finding customers, testing assumptions, shipping imperfect products, and learning how different company-building looks in the AI era.In our conversation, we explore what Sam had to unlearn when he moved from running a 600-person company back into an early-stage startup. We get into why Cuttable walked away from nearly $1 million in annual recurring revenue, how enterprise customers can pull a young company away from the product it actually needs to build, and why AI is shifting product and engineering teams from owning parts of a system to owning measurable outcomes.Key TakeawaysPast success can distort your judgment: Starting Cuttable reminded Sam that reputation means little if the product does not solve a problem customers will pay for.Experience does not transfer automatically: Sam could trust his instincts when building for engineers, but entering advertising required him to test assumptions and learn from customers.Revenue can hide the wrong product: Cuttable reached nearly $1 million in ARR while engineers were still manually doing work the product was supposed to automate.Taking the long view can require a reset: Sam and his co-founders released every customer, returned to zero revenue, and rebuilt around end-to-end automation.AI shifts the focus from tasks to outcomes: Instead of teaching AI to copy a human process, teams should define the desired result and let AI determine how to achieve it.Additional InsightsSpeed can be an advantage over scale: A Cloud Guru prepared courses before AWS certifications launched, then updated them using real exam feedback.Playfulness can strengthen a product: Short, entertaining lessons made cloud training easier to engage with and helped A Cloud Guru stand out.Paying customers provide stronger signals: Payment shows whether a problem matters enough to solve and makes the customer's feedback more meaningful.AI is changing team ownership: Cuttable is moving from teams that own system components to teams accountable for measurable customer outcomes.Founder optimism needs a counterweight: Glitch Capital uses analysts and experienced operators to challenge assumptions and add rigor to investment decisions.Episode HighlightsEpisode Highlights00:00 – Episode RecapSam reflects on starting again after a major exit and learning that customers care more about solving their problem than a founder's reputation.02:13 – Guest Introduction: Sam KroonenburgMeet Sam Kroonenburg, CEO and co-founder of Cuttable, co-founder of A Cloud Guru, and founder investor at Glitch Capital.03:29 – The Moment Technology ClickedSam traces his entrepreneurial journey back to receiving his first computer and learning to code through an online pen pal.09:11 – Winning Through Speed and PlaySam explains how A Cloud Guru used informed bets, rapid updates, and playful learning experiences to move faster than larger organizations.12:26 – Starting Again and Unlearning Founder InstinctMoving from a 600-person company to an early-stage startup forced Sam to test his assumptions and relearn how to earn customer trust.17:51 – Running a Startup Like a Large CompanySam initially brought too much structure, reporting, and sales pressure into Cuttable before refocusing on product-market fit.20:56 – Why Cuttable Went Back to ZeroAfter reaching nearly $1 million in ARR, Cuttable released every customer and rebuilt around end-to-end automation.27:48 – Why Paying Customers Change the SignalSam explains why payment reveals whether a problem matters enough to solve and makes customer feedback more meaningful.29:43 – Stop Teaching AI to Work Like a HumanCuttable learned to give AI the available data and desired outcome instead of forcing it to follow a prescribed human process.34:45 – Organizing Teams Around OutcomesSam explores why engineers focused on customer impact often embrace AI and how Cuttable is organizing teams around measurable outcomes.38:41 – Why Founder Optimism Needs a FilterSam explains how Glitch Capital balances founder optimism with analysts and experienced operators who challenge assumptions.42:03 – Smaller Teams and Bigger ImpactSam shares his optimism that AI will help smaller teams create impact at a scale that once required much larger organizations.FAQsQ1. What did Sam Kroonenburg have to unlearn after building A Cloud Guru?Sam had to unlearn the confidence and operating habits that came with previous success. At Cuttable, he found that reputation could not replace customer value, evidence, or the search for product-market fit.Q2. Why did Cuttable give up nearly $1 million in annual recurring revenue?Enterprise demands were pulling Cuttable toward custom work and manual intervention. When engineers began generating and fixing campaigns themselves, the team released those customers and rebuilt around end-to-end automation.Q3. How does Sam Kroonenburg think AI changes product development?Sam believes teams should spend less time telling AI how to perform a task and more time defining the desired outcome. AI can then use the available data to determine the best method.Q4. Why does Sam prefer feedback from paying customers?Payment shows that a problem matters enough to solve. Free users can offer feedback without genuinely valuing the product, while paying customers provide a stronger signal.Q5. How is AI changing the way Cuttable organizes engineering teams?Cuttable is organizing teams around measurable customer outcomes instead of software components. Teams can use AI and evaluation systems to improve those outcomes continuously.Useful ResourcesCuttable — Sam Kroonenburg's AI-powered creative production system for advertising.A Cloud Guru — The cloud computing education company co-founded by Sam and later acquired by Pluralsight.Glitch Capital — The Australia and New Zealand founders fund Sam started with fellow founders and operators.AWS re:Invent — Discussed in Sam's story about how A Cloud Guru prepared training for new AWS certifications at launch speed.Square Peg — Cuttable's investor, whose response to the company's decision to reset revenue reinforced Sam's understanding of seed-stage investing.Artificial Organizations — https://geni.us/artificialorgsRead Artificial Organizations? Leave a review on Amazon - https://www.amazon.com/review/create-review/ref=cm_cr_othr_d_wr_but_top?ie=UTF8&channel=glance-detail&asin=1067626328Follow Barry O'Reilly:LinkedIn: https://www.linkedin.com/in/barryoreillyWebsite: https://barryoreilly.comFacebook: https://www.facebook.com/barryoreillyauthor/X:

How cheap does a TV have to be before you stop asking what it knows about you? LG denies recording ambient conversations for ad targeting, but its other tracking practices leave plenty to discuss. Plus, Apple TV and Jean Smart clean up at the Emmys, streaming giants team up to lobby Washington, and AWS wants to put ten live feeds on one screen. Netflix prepares to share box-office numbers, IMDb makes room for digital creators, and a possible Get Smart reboot arrives with suspiciously good timing.This week on The FULL Experience: The Nude BombNext week: Battlestar Galactica (101 - "Saga of a Star World")Subscribe, get expanded show notes, and past episodes at http://Cordkillers.comSupport Cordkillers at http://Patreon.com/CordkillersYouTube: https://youtu.be/d71FfUfHZrU Hosted on Acast. See acast.com/privacy for more information.

How cheap does a TV have to be before you stop asking what it knows about you? LG denies recording ambient conversations for ad targeting, but its other tracking practices leave plenty to discuss. Plus, Apple TV and Jean Smart clean up at the Emmys, streaming giants team up to lobby Washington, and AWS wants to put ten live feeds on one screen. Netflix prepares to share box-office numbers, IMDb makes room for digital creators, and a possible Get Smart reboot arrives with suspiciously good timing.This week on The FULL Experience: The Nude BombNext week: Battlestar Galactica (101 - "Saga of a Star World")Subscribe, get expanded show notes, and past episodes at http://Cordkillers.comSupport Cordkillers at http://Patreon.com/CordkillersYouTube: https://youtu.be/d71FfUfHZrU Hosted on Acast. See acast.com/privacy for more information.

In this sponsored episode, Paul Delory of Gartner joins Kyler and Ned to discuss the reconciler pattern for operations and the shift toward continuous operations. Together they discuss how immutable infrastructure, policy as code, and platform engineering help bridge the gap between traditional IT and modern automation. They also highlight Gartner’s upcoming Infrastructure, Operations &... Read more »

Cloud Posse holds LIVE "Office Hours" every Wednesday to answer questions on all things related to AWS, DevOps, Terraform, Kubernetes, CI/CD. Register at https://cloudposse.com/office-hoursSupport the show

AWS – koryto PiSu za Tuska! | IPP #IPPTVNaŻywo #polityka #Tusk #rozliczenia #PiS ⛵️

Last week we sealed the heart of the kāfir and stood at the mouth of the third category. This week we step into it. Of the three types of people in Part One — the muttaqīn (Ayāt 2–5), the kāfir (Ayāt 6–7), and the munāfiq (Ayāt 8–20) — the hypocrite is given the longest passage by far. Thirteen ayāt against four and two. It is worth asking why before we read a single word of them.1. Why the Hypocrite Takes the Longest PassageTwo reasons. First, there are different types and levels of hypocrite. Second, and more telling, the munāfiq is simply hard to define. The person of taqwā is clear — good within, good without. The kāfir is clear — bad within, bad without. But the hypocrite is neither here nor there: good on the surface, corrupt underneath, and forever shifting between the two. Ambiguity needs more words to pin down than clarity does.2. The Word Munāfiq: The Tunnel of the DabbThe word comes from nafaq — a tunnel. But the image turns on the difference between a burrow and a tunnel. A rabbit's burrow has one opening: one way in, one way out, a door the animal must stand and defend because it has no other. The dabb, the desert lizard, digs a tunnel with two openings. When danger comes from one end, it bolts out the other. It never has to commit to a position; it always keeps an escape route.That is the hypocrite exactly. When the Muslims are winning, he says, “We are with you — one of you.” When the tide turns toward the Quraysh, he slips out the far exit: “We are your friends; we've been helping you all along.” A bestie to both — though the word best can only ever have one.There is a fitting detail in how the Arabs still hunt the dabb. Because the tunnel has many mouths, it is never a one-man job. A group drives into the desert, finds the holes, and floods them with water from a hose. Not knowing which exit the animal will take, they watch every opening at once — and take it the moment it surfaces. The very feature meant to keep it safe is what exposes it. (A note in passing: the dabb is ḥalāl, though the Prophet ﷺ did not eat it himself, as it was unfamiliar to his people.)3. How the Hypocrites Came to BeWhen the Muslims made the Hijrah, they were not yet strong. In that first year Madīnah held three groups: the Muslims — some 300-plus men, perhaps close to a thousand souls with their families, in a city of six or seven thousand, a ruling minority; the Jews, in three tribes (the Qaynuqāʿ, the Naḍīr, and the Qurayẓah); and the pagans, still free to worship their idols. There were no Christians in Madīnah.Here a point of definition matters. When the moment of decision came, the pagans faced a choice the Jews did not — because being a Jew is a matter of ethnicity as well as religion. You can change your religion; you cannot change your lineage, any more than a Malay can decide to be Chinese. So the religious conversions that followed came from the pagans, whose religion put no such barrier in the way.The decisive moment was the Battle of Badr, in the second year of Hijrah. 313 Muslims, badly equipped — not all of them even had swords, and those they had were feeble, because they had never set out expecting war — faced roughly a thousand Quraysh, armed to the hilt, one of the largest armies Arabia had yet seen. And the Muslims won decisively; the leading men of Quraysh were killed. The politics of the peninsula turned in a day. Islam was here to stay.Badr is also a lesson in how planning and reliance on Allah fit together. The Muslims were aided by angels — but you do not put angels in your plan. You make du'ā for help and Allah sends it however He wills, but you prepare with the means actually in front of you. You cannot study three chapters of ten and expect an angel to whisper the rest in your ear during the exam. Do your utmost; then trust Him for what lies beyond your reach.After Badr, the pagans understood there was no future on the losing side, and no ethnic wall to shelter behind as the Jews had. Their only way to keep standing and influence was to profess Islam outwardly. For many, the profession was hollow — and this is the origin of the hypocrites. There were none in the first year of Hijrah; they appeared only in the second, once outward Islam became the price of relevance.4. The Leader of the Hypocrites: ʿAbdullāh ibn UbayyThe munāfiqūn had a head: ʿAbdullāh ibn Ubayy ibn Salūl. To understand him, return to pre-Islamic Madīnah, then called Yathrib — home to Arabs and Jews. The Arabs were two main tribes, the Aws and the Khazraj, locked in a feud that had run for decades and killed off the senior leaders on both sides. It was exhaustion with that un-winnable war that finally led them to invite the Prophet ﷺ from Makkah to lead them.Ibn Ubayy was the most senior figure left standing, and he had expected the leadership of Madīnah to fall to him by default. But the rival tribe would never accept a ruler drawn from the enemy they had fought for a generation — so the people reached past their own factions for a neutral leader, and invited the Prophet ﷺ. Ibn Ubayy was left jealous and bitter: the leadership was supposed to be mine. He and his followers stayed pagan at first, betting the Muslims would soon be gone. When Badr proved otherwise, he “accepted” Islam with his tongue while nursing the grievance in his heart — and so led the hypocrites, later feeding the weak points of Madīnah to the Quraysh, telling each side what it wanted to hear.5. Ayah 8 — “We believe” (but they do not)وَمِنَ ٱلنَّاسِ مَن يَقُولُ ءَامَنَّا بِٱللَّهِ وَبِٱلْيَوْمِ ٱلْـَٔاخِرِ وَمَا هُم بِمُؤْمِنِينَWa mina al-nāsi man yaqūlu āmannā billāhi wa bil-yawmi al-ākhiri wa mā hum bi-mu'minīn.“And among the people are those who say, ‘We believe in Allah and in the Last Day,' but they are not believers.”Walking the words: wa — and; min al-nās — among the people; man yaqūlu — those who say; āmannā billāhi wa bil-yawmi al-ākhir — we believe in Allah and the Last Day; wa mā hum bi-mu'minīn — but they are not believers. They claim faith in Allah and the Hereafter, and Allah Himself overturns the claim: they never had īmān at all. The mouth says one thing; the heart holds another.From this comes a principle worth carrying. The Prophet ﷺ and many companions knew the hypocrites — Jibrīl named them through revelation — yet Ibn Ubayy was never punished for his hypocrisy. Because we judge people by their outward actions, not their intentions. Intention is known to Allah alone; it is a matter between a person and their Lord. The Prophet ﷺ had revelation; we do not. So the lesson is a careful balance: take people at face value — do not accuse, do not presume to read hearts — but stay discerning. Where the signs of untrustworthiness are clear, you guard yourself accordingly, without ever making an accusation about what lies inside another person.6. Ayah 9 — The Deception That Reboundsيُخَـٰدِعُونَ ٱللَّهَ وَٱلَّذِينَ ءَامَنُوا۟ وَمَا يَخْدَعُونَ إِلَّآ أَنفُسَهُمْ وَمَا يَشْعُرُونَYukhādiʿūna Allāha wa alladhīna āmanū, wa mā yakhdaʿūna illā anfusahum wa mā yashʿurūn.“They think to deceive Allah and those who believe, but they deceive none but themselves — and they perceive it not.”They imagine they can slip their disbelief past Allah — that He does not see the pretence — and past the believers with Him. But the deception lands on no one but themselves; they are the ones who end at the losing end. And the closing phrase, wa mā yashʿurūn — “they do not even perceive it” — is the sharpest edge of the ayah: the trap has closed on them, and they cannot even feel it.7. Ayah 10 — The Disease of the Heartفِى قُلُوبِهِم مَّرَضٌ فَزَادَهُمُ ٱللَّهُ مَرَضًا وَلَهُمْ عَذَابٌ أَلِيمٌۢ بِمَا كَانُوا۟ يَكْذِبُونَFī qulūbihim maraḍun fa-zādahumu Allāhu maraḍā, wa lahum ʿadhābun alīmun bimā kānū yakdhibūn.“In their hearts is a disease, so Allah has increased their disease; and for them is a painful punishment for the lies they used to tell.”Allah names hypocrisy a disease (maraḍ) of the heart — and rather than cure it, He increases it. A quick distinction of terms: nifāq is the hypocrisy; munāfiq is the hypocrite himself. For them is ʿadhāb alīm, a painful punishment, earned by their persistent lying.The word alīm carries more than the translation shows, and it turns on pronunciation. ʿAlīm, opened with an ʿayn, means “most knowledgeable.” Alīm, opened with a hamzah, means “painful.” The whole meaning rides on that first letter — which is why precise recitation (makhraj) is a necessity, not a refinement.The root of pain is alam; alīm is its intensified form. That extra yā' — the -īm pattern — is a form of hyperbole: not exaggeration in the sense of something untrue, but intensification to the extreme. It is the same pattern as Ar-Raḥīm, which is not merely “merciful” but extremely merciful. So alīm is not just pain, but pain at its utmost.And the pattern carries a second dimension: it is continuously increasing. A punishment that does not merely hurt but keeps growing worse. The reason Allah frames it this way cuts against something we know from experience — in this world, pain eases as we grow used to it. The first time you stretch into the splits it feels like torture; do it daily and the body adjusts until it is nothing. Walk fifteen kilometres in forty-degree heat with long stretches of no shade, and the five-minute walk to the masjid the next day feels like nothing at all. We adapt. The punishment of Jahannam is built so that no one ever adapts: each time the person thinks “I can bear this now,” it deepens; “I think I've adjusted,” and it deepens again — continuous, escalating, with no floor to settle onto.The same -īm pattern, turned toward mercy, gives Ar-Raḥīm — and here the contrast is worth holding. Ar-Raḥmān is the mercy Allah extends to everyone in this world; Ar-Raḥīm is the mercy reserved for the believers in Jannah. And like alīm, it is ever-increasing, but toward the good. In this world even what we love grows stale; we get used to it and it becomes the new normal. In Jannah the delight only ever improves — better, and better, and better, without end.8. ʿAẓīm vs Alīm: Whose Punishment Is Worse?Set the two endings side by side. Ayah 7, of the kāfir, closes: wa lahum ʿadhābun ʿaẓīm— “a great punishment.” Ayah 10, of the munāfiq, closes: wa lahum ʿadhābun alīm — “a painful punishment.” Note that ʿaẓīm, “great,” is a neutral intensifier: one can be greatly foolish or greatly brilliant. It magnifies without saying good or bad.So whose is worse? On the strength of the language, the munāfiq's. ʿAẓīm describes a punishment that is great; alīm describes one that is painful and continuously increasing. The hypocrite's does not merely match the disbeliever's in scale — it deepens without end. And fittingly so: the hypocrite knew the truth, professed it with his tongue, and betrayed it in his heart.Next week, in shā' Allāh, we continue into the hypocrites' passage — and our quiz will cover up to Ayah 10, including the characteristics of the People of Taqwā and the definitions of the kāfir, so keep them memorized. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.grounded.day/subscribe

Topics covered in this episode: Pandas Should Go Extinct Pydantic-pint puts real-world units in your Pydantic models How Libraries Run Rust Inside Python (With PyO3) AWS acquires DuckLabs Extras Joke Watch on YouTube Sponsored by Logfire from Pydantic: pythonbytes.fm/logfire Connect with the hosts Michael: Mastodon / BlueSky / X / LinkedIn Calvin: Mastodon / BlueSky / X / LinkedIn Show: Mastodon / BlueSky / X Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesday at 7am PT. Older video versions available there too. Finally, if you want an artisanal digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it. Calvin #1: Pandas Should Go Extinct Pandas' slowness pushes teams toward "Big Data" tools (Spark, Databricks) they don't actually need — most workloads never hit true Big Data scale Amazon Redshift telemetry: ~95% of tables are under 100GB, ~87% of queries touch 80GB or less — that's "Medium Data," not Big Data Polars and DuckDB fill that gap: single-machine, fast, no cluster required 1 Billion Row Challenge benchmark: Pandas took 4m28s vs. Polars 5.04s and DuckDB 5.19s — DuckDB also used 19x less memory On a real-world NYC taxi dataset (3GB parquet), pure DuckDB ran 2x faster than pure Pandas while using a fraction of the RAM Bonus: Apache Arrow lets you pass data between Pandas/Polars/DuckDB with zero copying, so trying them out doesn't mean a full rewrite Michael #2: Pydantic-pint puts real-world units in your Pydantic models Pydantic-pint bridges Pydantic and Pint so models can validate physical quantities like 4m or 12 meters instead of bare floats. Fields annotated with PydanticPintQuantity parse user input, convert between compatible units, and serialize quantities back out as strings. That closes a real gap for anything consuming API payloads, config files, or sensor data with measurements, letting you enforce units at the validation boundary instead of hoping every caller remembered them. via PyCoder's Weekly newsletter Unit mix-ups have literally crashed spacecraft; now your Pydantic models can refuse them at the door. Annotate a field as Annotated[Quantity, PydanticPintQuantity('km')] and inputs like 12 meters arrive auto-converted to kilometers Validation covers string, numeric, and quantity inputs, and model_dump_json serializes quantities as readable unit strings Installable from PyPI as pydantic-pint, MIT licensed, with docs at pydantic-pint.readthedocs.io Early-stage solo project at version 0.4, so API stability and maintenance are open questions worth discussing Calvin #3: How Libraries Run Rust Inside Python (With PyO3) Pydantic v2's validation core (pydantic-core) is Rust under the hood, built with PyO3 — this post shows how that bridge actually works via a small hand-built JSON parser Four steps to get Rust into Python: write a normal Rust module, annotate with PyO3 macros (#[pyfunction], #[pymodule]), compile/install with maturin, then just import it The parser builds a Rust tree first — Python never touches it until the boundary crossing Key insight: converting the Rust result into Python objects (.into_pyobject) is often the expensive part, not the parsing — 100,000 JSON values means ~100,000 Python objects built after parsing's already done Errors cross the boundary too: Rust's typed errors convert into real Python exceptions (ValueError, FileNotFoundError) via From/?, so callers get clean Python semantics Takeaway for anyone porting Rust in: if you're returning a scalar, don't sweat it; if you're returning a big structure, profile the boundary — that's the real cost, not the algorithm Michael #4: AWS acquires DuckLabs Thank you Dylan McConnell. What does this mean for the DuckDB ecosystem? DuckDB is the open-source in-process analytical SQL engine. MIT licensed. The IP is not owned by any company - it's held by the nonprofit DuckDB Foundation, which was created when the team spun out of CWI Amsterdam. Peter Boncz, the CWI representative on the Foundation board, describes it as the entity that holds all IP of open-source DuckDB. DuckLabs (ducklabs.com) is the company, formerly branded DuckDB Labs. Founded a little over five years ago by Hannes Mühleisen and Mark Raasveldt to give the DuckDB team a stable long-term home, bootstrapped deliberately instead of taking VC, grown to 30+ people in Amsterdam, funded by support and feature-prioritization contracts. It employs the core devs. It does not own DuckDB. DuckLake is one of three projects DuckLabs builds, what they call the Duck Stack: DuckDB, DuckLake, and Quack. DuckLake is the lakehouse format that puts catalog metadata in a SQL database instead of in files on object storage. Quack is newer - an RPC-style protocol that turns DuckDB into a client-server system where both ends are DuckDB instances, slated to stabilize in DuckDB v2.0 in September 2026. MotherDuck is a separate Seattle company, Jordan Tigani's, selling serverless hosted DuckDB. It was started in partnership with DuckDB Labs and has worked closely with Hannes and Mark for four years. It contracted DuckLabs for engineering work and contributes heavily upstream - three of its engineers are among the top 10 outside contributors to DuckDB. It also sells its own DuckLake offering. Customer and collaborator, never owner. What the AWS post changes. Amazon bought the company, not the project. DuckLabs joined AWS effective September 1, with the process concluding August 31, 2026. Hannes and Mark keep leading the team and the project's technical direction, the team stays in Amsterdam, and DuckDB stays MIT under the Foundation. AWS gets the people and a direct line to the roadmap. The license protects your code, not your priorities. Three second-order effects worth tracking: The Foundation board is the real question. It has three directors: Mühleisen, Raasveldt, and Boncz. Two now work for AWS. Commentary on the deal has focused on exactly this - the license protects the code, not the roadmap. The announced counterweight is governance: a technical advisory board on the Foundation, and opening the extension stack so extensions signed by other developers can run in DuckDB. MotherDuck immediately moved into the business DuckLabs vacated. It now sells DuckDB enterprise support, which it had avoided because it didn't want to compete with DuckLabs' business model, and says it has explicit blessing from Hannes and Mark now that they're joining Amazon. It also bought Tower.dev the day before the AWS announcement. Everyone expects an AWS DuckDB service. Tigani says Amazon will likely release one eventually, and welcomes the competition, citing Redshift's failure to slow Snowflake on AWS. The groundwork is already visible: Amazon Quick uses DuckDB to query S3 Tables and has processed over 2.5B queries with it since launching in October 2025. The DuckLake angle is the one to watch. AWS is heavily committed to Iceberg through S3 Tables, and it just acquired the team behind a competing lakehouse format. The stated plan is to use DuckDB, DuckLake, and Quack together to power a new generation of data services, but which format wins internal priority is unannounced. Extras Calvin: astral-sh/uv 0.12.12: code-signed release binaries

Keith McCall is building a company that watches the Earth from above. Omniris pulls imagery from drones, satellites, and IoT sensors, overlays it on a map, and adds the one thing that makes data powerful  time. Capture the same field or cell tower ten times across a year and you get a living database, a digital twin more useful than anything sitting in a spreadsheet. His network of 4,000 independent drone pilots has flown Walmart's headquarters, Amazon distribution centers, 11,000 Verizon cell towers, and solar farms around the world.  Keith is the CEO of Omniris, along with the ag-tech company Pollen Systems and the wine venture Everyvine. He and Jason get into why he ripped out a $2 billion incumbent and bet on open source, how he handles data sovereignty across Azure, AWS, and on-premise servers from Saudi Arabia to Chile, and why he thinks the billions being poured into AI valuations could evaporate faster than anyone expects. We also discuss: Why he went open source to scale past a $2 billion competitor The AI valuation bubble and how Chinese model distillation could wipe it out Smart cities. Why Seattle's cameras, drones, and traffic lights aren't on one geospatial layer The coming food crisis and the aging-farmer knowledge problem behind his ag-tech work Hiring for communication, collaboration, and compassion over pedigree Ranking family offices first and venture capital last when raising money    Keith's links: LinkedIn: https://www.linkedin.com/in/keithmccall/ Omniris: https://omniris.world/ Pollen Systems: https://www.pollensystems.com/ Everyvine: http://www.everyvine.com Eastside Entrepreneurs: https://eastent.org/ Jason links: LinkedIn: https://www.linkedin.com/in/jasoncavness Follow the show so you don't miss an episode.

AI is all anyone can talk about right now, but most of us are just getting started with it while the giants have been building it for two decades. In this episode I sat down with Sneha Shah, CEO and co-founder of Hazel AI, who spent nearly 20 years at Amazon and Google as the engineer behind the scenes. She was on the team that built Amazon same-day delivery and scaled it to ten countries, then went to Google as a founding engineer on Cloud Spanner, the global database that powers companies like Deutsche Bank and Nintendo, before building Vertex AI and scaling it into Gemini Enterprise. We broke down how AI actually gets built (yes, it is real people writing real code), why Amazon delivery has always been a losing model, why AWS is where the money is, and the difference between knowledge and wisdom in an LLM. Then we got into Hazel AI, the engine she is building underneath the biggest tech consulting firms on the planet, and the honest conversation everyone is avoiding: which jobs AI is going to take, which ones it is going to create, and why the opportunity has never been bigger for the people willing to get uncomfortable and level up. If you want to hear where AI is going from someone who has actually been in the trenches instead of another influencer guessing, this one is for you. About Guest: Sneha Shah is the CEO and co-founder of Hazel AI, an Autonomous AI Modernization OS that powers global system integrators as they take Global 2000 enterprises from cloud native to AI native. Before founding Hazel, Sneha spent nearly two decades building at the largest scale on the planet. She started her career at Amazon straight out of Carnegie Mellon University, where she was part of the team that built same-day delivery and scaled it across ten countries. She then spent almost a decade at Google Cloud as a founding engineer on Cloud Spanner, the globally distributed database used by companies like Deutsche Bank and Nintendo, growing the team from four to hundreds and the product to over 100 million in scale. She went on to build Vertex AI, Google's flagship AI platform, and scale it into Gemini Enterprise. Hazel AI now works with five of the top ten global system integrators and serves over $10 billion in business across retail, manufacturing, and agriculture. Sneha is based in the San Francisco Bay Area. Guest Links and Socials: Website: https://www.gethazel.dev Platform sign-up: https://gethazel.ai LinkedIn: https://www.linkedin.com/in/snehashah/ Contact: sneha@gethazel.ai About Justin: Justin Colby is the host of The Entrepreneur DNA and The M.O.R.E Show podcasts and a best-selling author. He is a serial entrepreneur and a seasoned real estate investor with over 20 years of experience. Driven by a passion to help entrepreneurs thrive, Justin created the Entrepreneur DNA community to support business owners in building wealth, systems, and long-term freedom. Through his podcasts, books, education platforms, and hands-on mentorship, he continues to help entrepreneurs scale with clarity and confidence. Connect with Justin: Instagram: @thejustincolby YouTube: Justin Colby TikTok: @justincolbytsof LinkedIn: Justin Colby Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Don’t get left behind in the AI revolution. Subscribe to our Newsletter: https://theultimatepartner.com/ebook-subscribe/ Check Out UPX: https://theultimatepartner.com/experience/ In this powerful episode, Vince Menzione sits down with Rebecca Jones of Bridge Partners and Mark Yaphe, Head of Consulting Partners for AWS, to uncover how AI is fundamentally rewiring the partner ecosystem. They explore the urgent shift from 90% stalled AI pilots to a new era of rapid execution, warning against the trap of “shiny object” syndrome. By unpacking the necessity of a “builder mindset” and a product-focused approach, this discussion reveals exactly what top-performing companies are doing to collapse six-month development cycles into four weeks and secure their place in the 2026 market landscape. Key Takeaways The transition from on-prem to cloud and marketplace is now entirely focused on AI transformation. Top companies approach AI with a product mindset rather than running scattershot pilots. Empowering frontline teams with a “builder mindset” can collapse solution cycles from six months to four weeks. Partners must avoid the $260 billion AI “FOMO” trap by specializing in specific industries and workflows rather than trying to do everything. Evaluating the “highest and best use” of AI models like Claude is essential for managing token economics and ROI. Thriving through AI disruption requires cultivating a strong growth mindset and prioritizing human connection and critical thinking. If you're ready to lead through change, elevate your business, and achieve extraordinary outcomes through the power of partnership—this is your community. At Ultimate Partner® we want leaders like you to join us in the Ultimate Partner Experience – where transformation begins. Key Tags AI transformation, AWS partner ecosystem, hyperscaler alignment, builder mindset, product mindset implementation, Bridge Partners insights, GenAI solution cycles, AI token economics, Claude model utilization, GSI strategy, 2026 ecosystem shift, AI ROI measurement, agentic tools, workflow specialization. Transcript Rebecca Jones and Mark Yaphe AUDIO EPISODE [00:00:00] Rebecca Jones: You can either, um, think about being disrupted or being a disruptor. [00:00:07] Vince Menzione: You can feel it happening. The ecosystem is shifting beneath us the way hyperscalers are partnering, how AI is remaking the channel. And what it means to win in 2026. [00:00:18] Vince Menzione: Welcome to the Ultimate Partner Podcast. I’m Vince Menzi, own your host. [00:00:23] Vince Menzione: And each week I sit down with leaders at the intersection of [00:00:26] Vince Menzione: technology, partnerships and outcomes, the voices shaping how ecosystems actually work. We talk about what’s real, what’s changing, and what it takes to lead in this era where the partner channel isn’t just part of the strategy. It is the strategy because being in the room changes everything. [00:00:45] Vince Menzione: Let’s start. We have another incredible session today, right? So I get to invite another friend of, of ultimate partner who’s been around for a while and, uh, it’s just absolutely amazing. Rebecca has been in the studio, she’s been at, how many of events have you been with? Fourth, fourth one, and I’m gonna have you introduce Mark as well. [00:01:10] Vince Menzione: So come on, on stage. Rebecca. Rebecca Jones to many of you know. [00:01:14] Rebecca Jones: Thank you, sir. [00:01:15] Vince Menzione: Good to see you. Good to see you. And Mark, great, great to have you. I want to have you, Richard, we’ll have you, Rebecca’s gonna introduce you and then we want you to introduce yourself as well, sir. [00:01:23] Rebecca Jones: Wonderful. Well, [00:01:24] Vince Menzione: and another AWS exec. [00:01:26] Vince Menzione: I love this. Like, I know. Yeah, we’re finishing out the day Strong. [00:01:28] Rebecca Jones: Well, Vince, I have to say, you’ve got me, um, the last time we got together, it was the last session before happy hour. So I guess we’re closing. [00:01:36] Vince Menzione: Well, you know, we’re gonna close us [00:01:38] Rebecca Jones: out [00:01:38] Vince Menzione: really nicely. Know we, yeah. We’re serving Bloody Mary’s, by the way, while you’re guys are up here. [00:01:42] Vince Menzione: No. Good. [00:01:42] Rebecca Jones: So, um, we’re so excited to have Mark. Thank you, mark, for joining us here. Um, head of consulting partners for AWS and, uh. We’re gonna close this down, aren’t we? I love [00:01:54] Vince Menzione: it. I love it. Yes. I’m looking forward to it. [00:01:56] Rebecca Jones: Okay. [00:01:56] Vince Menzione: So Mark’s well, welcome. Good to have you. [00:01:58] Rebecca Jones: Yeah. Do you wanna take a seat? [00:02:00] Vince Menzione: Uh, yeah, [00:02:00] Rebecca Jones: please do. [00:02:01] Rebecca Jones: All right. [00:02:01] Vince Menzione: Please do. I’m morphing the pillows up, by the way. [00:02:05] Rebecca Jones: Oh, are you [00:02:05] Vince Menzione: by the way, for those of who don’t know, these got shipped from my house because we got Oh, I was wondering. It’s hard to find, but yeah. Yeah, they’re, we take them from event to event. It’s so funny to have them. But I wanna, well, thank you for both being here. [00:02:17] Rebecca Jones: Yes. [00:02:18] Vince Menzione: I think it’d probably be helpful for those who don’t know, bridge Of course. Maybe just spend a moment because I know you well. [00:02:23] Rebecca Jones: Yeah. [00:02:23] Vince Menzione: And we know the organization well, those of us. Those of us. [00:02:26] Rebecca Jones: But for me, uh, so let me talk to you a little bit about Bridge Partners and my role, um, the company has been around for almost two decades. [00:02:34] Rebecca Jones: Yeah. And so when you think about the transformation that’s happened within the tech industry. And our primary focus is the tech industry. Uh, and within that we focus on enterprise companies and we help them with product go to market and how they scale that through partners. Yeah. Uh, so that’s given us a really interesting and, uh, vantage point around the transformations from on-prem to cloud, cloud to marketplace and now marketplace and the transformation with ai. [00:03:04] Vince Menzione: I feel like you’re the McKenzie of the, of the partner business. Like I, [00:03:07] Rebecca Jones: I like that. [00:03:08] Vince Menzione: Can we get that? [00:03:09] Rebecca Jones: Yeah. [00:03:10] Vince Menzione: I’ll, I’ll, I’ll sign an agreement with you, but I really do, I feel like as we work together, bridge was always like the organization we bring in to help us. Solve the big issues. Yeah. Like that I think about your organization. [00:03:20] Vince Menzione: Yeah. And Mark, talk to me about Global Consulting services. Sure. So is it all GSIs? Is it, [00:03:24] Mark Yaphe: uh, so I head up, uh, global Consulting Partner Marketing. Okay. So I focus really on, on two key categories for the, the more sig larger, uh, GSIs. Uh, I’ve got a team that actually partners very closely with them. Nice. [00:03:36] Mark Yaphe: That helps them develop the right strategies, go to market approaches, nice to unlock the opportunity. And then for the full consulting community, I look at those mechanisms. Go to market approach is leveraging marketplace to help our whole consulting community become successful with AWS. [00:03:51] Vince Menzione: And we’ve got GSIs in the room here, which is kind of cool actually. [00:03:53] Vince Menzione: Yeah. Um, where do we wanna start? Let’s, let’s, [00:03:57] Rebecca Jones: well, yeah, we’ve got a good list of questions to go through. How’s everybody feeling? We’re we’re good? We’re awake. One more session, everyone. Alright. Okay. [00:04:09] Vince Menzione: So Rebecca, uh, across the organizations you work with. What are you seeing from the highest ’cause? I, I say you’re like the McKinsey. [00:04:16] Vince Menzione: What are you seeing from the highest performing companies? Yeah, that they do differently. When it comes to turning your go-to market strategy into outcomes? [00:04:23] Rebecca Jones: Yeah. Um, I will say the most important thing that we’re seeing from companies is they’re asking different questions, fundamentally different questions when it comes to ai. [00:04:34] Rebecca Jones: Interesting. [00:04:34] Vince Menzione: What do you mean by that? [00:04:35] Rebecca Jones: Well, we, we talked a lot this morning about there’s never been higher access, and I’ll say general adoption for tools and technology. There was a great stat this morning. Uh, I think Jay shared that, uh, from MIT. [00:04:50] Vince Menzione: We keep looking there as if he’s still [00:04:51] Rebecca Jones: sitting there. [00:04:51] Rebecca Jones: Yeah, I’m looking. Where was Jay? He, he was all over the place. Um, there was a great stat from MIT that there was, you know, if you looked at last year, 90% of pilots. Were stuck and they weren’t going anywhere. And now that’s dropped down to 70%. So there’s movement and transformation. And so when I think about that, and when I go back to the types of questions leaders are asking, um, that are really moving ahead, they’re looking at operating systems differently and they’re looking at, um. [00:05:25] Rebecca Jones: They’re asking the questions on where should I apply AI within those work streams, um, and within those operating systems, and the way in which they’re approaching that is with a product mindset. So that is fundamentally different than just the scattershot of let’s just do pilots everywhere. [00:05:44] Vince Menzione: Yeah. You’ve talked about product, uh, mindset with me as well. [00:05:48] Rebecca Jones: Yeah. [00:05:48] Vince Menzione: And I think we were gonna talk about builder mindset as well, mark, that that is a kind of a different point of view. When you think about moving from strategy to execution, how does that mindset show up inside teams and organizations? [00:06:00] Mark Yaphe: No, absolutely. Yeah. You know, the notion of the builder mindset is about, uh, taking the notion of innovation and pushing it out to the edge. [00:06:07] Mark Yaphe: Of the organization, um, the greatest ideas for innovation, the greatest things that will help you scale. They’re in the minds of your customers and the people that can best understand them and best address ’em. They’re your teams. Yeah. Your, your customer teams or your technical teams, but unlocking it. You, you want these teams to do more than just have the conversations and understand needs. [00:06:28] Mark Yaphe: You want them to be tooled and equipped to build. Yeah. So the ones that are right in front of the customers. In that moment of need where they say, I’ve got these offerings and these motions, and it gets me this far, but if I could only do a little bit more, I could delight them. I could really power this up. [00:06:45] Mark Yaphe: And so you wanna unlock that. You want to give them the tools to build, to build the POC to address specific, uh, options in the meeting. And then when they’re showing some success, show the rest of the organization how they can scale that. [00:06:58] Vince Menzione: How do you think about, because I think about big GSIs. Having huge organizations like Accenture has half a million people, and then you have customer teams that may not, are, may not be as fluent in the technology side of things. [00:07:13] Vince Menzione: Like how do you make sure that’s getting from the customer all the way to the right people in the organization and driving that loaded question. I know. [00:07:20] Mark Yaphe: No, I, I, um, you, you, you want to think about how that process works. Yeah. And there are parts of the organization. That define how do we get go to market offers in motions out to the field. [00:07:34] Mark Yaphe: Um, and they look at the whole thing and they say, well, how effective are we and how quickly can we cycle through? Yes. These activities. There’s one partner I worked with, um, they looked at this and they measure the cycle time. How long does it take me to get from pushing on an offer? Working with customers, getting feedback, and then creating new updates. [00:07:53] Mark Yaphe: A long, long time ago, like two years ago, this would take, it was a hundred [00:07:57] Vince Menzione: years ago in AI terms. [00:07:59] Mark Yaphe: Well, that’s basically it. This took about five to six months. They get about two revs a year. Now. They literally implemented a geni solution that number one uses geni to push it out to the teams, makes it bespoke on an engagement by engagement basis. [00:08:14] Mark Yaphe: It makes it relevant for their industries and their use cases. And that same tool is the feedback mechanism. So in real time it’s providing feedback. So they’ve collapsed six month cycle times to four weeks. And the punchline here is we talked about builder teams. The people that figured out they needed the solution, built the solution, and piloted the solutions were the builder teams. [00:08:36] Mark Yaphe: They were the people working with the customers. [00:08:38] Vince Menzione: I love it. Yeah, I love it. Anything to add to that? Rebecca, I know you work again, being the McKinsey of the, of the partner world. [00:08:46] Rebecca Jones: Well, I’ll, I [00:08:47] Mark Yaphe: It’s gonna stick, [00:08:47] Rebecca Jones: stick. It’s [00:08:48] Vince Menzione: gonna [00:08:49] Rebecca Jones: stick. You say it three times, that’s stick. No, I, you know, mark just hit on some really important things with the customer mind. [00:08:57] Rebecca Jones: You’re really looking at what outcomes are you trying to drive for those customers and that builder mindset, you, you’re going to hear a lot about that because companies need, as you transform, you really need to be thinking differently. And transformation takes quite a while. And while there is massive opportunity and you see the, the quickness you have to have that long-term vision and then be able to work backwards from that. [00:09:21] Rebecca Jones: And so I couldn’t agree more with the, the focus on customer outcomes. [00:09:26] Vince Menzione: So we’re in a very interesting, I’ll call it, almost a seminal point, although that’s overused in terms of where we are with AI today, right? I you mentioned like two years, feels like 10 years. Yeah. Ago, right? I mean, we’ve seen such transformation happening, but it also doesn’t feel like organizations are keeping, like, I, I feel like small SMBs actually are further ahead because they, they have to be agile, but the bigger organizations are still trying to figure some things out, right? [00:09:53] Vince Menzione: So. What needs to change around organizations, culture management processes? Like how do we bring, how do we bring everyone along on this journey? [00:10:04] Mark Yaphe: There’s a lot that needs to happen. Um, [00:10:07] Vince Menzione: yeah. [00:10:08] Mark Yaphe: One thing that struck, there’s a lot of things I, I wanted to anchor on. One that Yeah, please. It could be a relevant conversation. [00:10:13] Mark Yaphe: Both, um, as part of your, uh, partner organizations delivering outcomes to customers. And, um, it’s about focusing on the business outcomes. It can be very easy, uh, to talk about the technology and the services, but day to day, the sales organization is going into solve customer problems. They’re meeting line of business leaders in specific industries who have very specific business problems to tackle. [00:10:42] Mark Yaphe: And I think one thing that organizations can do is impress upon them that it’s critical to understand. What are the business problems that we solve for our customers that we’re serving? What are those use cases? What are the drivers for it? In the role that I’m doing in an organization, how does that move the needle? [00:10:58] Guest: Yeah. [00:10:58] Mark Yaphe: For the business outcomes, it’s, it’s not dissimilar to other things, and perhaps it’s a little bit of a pivot, but always thinking about business outcomes, I think is, um, a little bit of a change that needs to be instilled within [00:11:10] Vince Menzione: what, what are the best doing better, and where are you seeing the gaps? [00:11:16] Mark Yaphe: Couple of areas, uh, one area, um, nobody knows everything. Yeah. Nobody’s got all the knowledge. [00:11:23] Vince Menzione: Right. [00:11:23] Mark Yaphe: And so rely on your ecosystem of partners and stakeholders. Yeah. Recognize you’ll only have so much information, um, and reach out, whether it’s to your technology partners, your business partners, your hyperscalers AWS to find out what am I missing. [00:11:38] Guest: Yeah. [00:11:38] Mark Yaphe: Um, again, many years, you know, a hundred years ago, two years, two years ago, um. We’d have these conversations about, well, what use cases are you seeing and what business problems are you solving? But, but those would be in scheduled meetings quarterly. Now there are agenda items on weekly standards. [00:11:55] Mark Yaphe: They’re happening every single week. What are you seeing? What are you seeing? And further, I’ve seen some gen AI and agent solutions that actually automate how that information flows to, to make it, to accelerate. [00:12:06] Vince Menzione: Yeah, it’s, it’s absolutely amazing. Yeah. Anything on, I mean, certainly you’ve got a perspective ’cause you’re working with these organizations. [00:12:13] Rebecca Jones: I have a couple thoughts on this specifically for the partner organizations and the partner companies here. I can understand there’s a lot of, you know, we looked at a stat earlier about the AI partner opportunity and it was. $260 billion somewhere in that bracket. And that can create maybe some fomo, you know, maybe, uh, let’s go after everything in this area. [00:12:37] Rebecca Jones: Yes. And not pick and choose [00:12:39] Mark Yaphe: a [00:12:39] Rebecca Jones: shiny object. Shiny object and not prioritize. And it’s actually the opposite. It’s really understanding where your strengths are in the market. Um, who’s in your partner ecosystem? What are you bringing to market? Are you, uh, a tech company that are looking to break? Bridge and bring out services or your services company, and now that can build product. [00:13:01] Rebecca Jones: But really understanding your opportunity. What industry do you play, what specialization do you have? And go really deep and then know how to augment your partners and the ecosystem around you to make you stronger and better for the customer. So with that market opportunity, which is. Tremendous, how do you focus and prioritize? [00:13:21] Rebecca Jones: And that’s where I have observed partners. Oh, I’m a little bit here, a little bit there, a little bit here. And, and, uh, I would be curious, I mean, that’s probably pretty hard for you if a partner shows up and they’re a little bit of everything. [00:13:34] Mark Yaphe: Well, I, I resonated with a point that you made before. Yeah. I, I’ve spent, um, half my time at AWS on the consulting side working with enterprise customers, the us half the partners. [00:13:43] Mark Yaphe: It’s critical that partners understand what’s unique about them. [00:13:45] Exactly. [00:13:46] Rebecca Jones: Yeah. [00:13:47] Mark Yaphe: You it. I mean, everybody here, they’re looking at cloud migrations and modernizations and agentic, but that’s kind of part of the noise. You’ve gotta know what uniquely you do in an organization to deliver value. Are you developing supply chain for transportation companies or drug acceleration pipelines for. [00:14:06] Mark Yaphe: Pharmaceuticals. Yeah. Starting with that anchoring on your differences, I think is, is really important. [00:14:11] Vince Menzione: When I first started in the partner world, that was one of the biggest challenges and dilemmas, and I’m sure you still see it today, where I do all things. You know the partner that does the big SI that does everything, they have all the certifications. [00:14:24] Vince Menzione: I have 10,000 people trained on every technology certification, right. And then like, well what do you do? Like, and they can’t clarify. Right. Have that conversation. [00:14:33] Mark Yaphe: And then how do people, customers, [00:14:35] Vince Menzione: yeah. [00:14:35] Mark Yaphe: Or sales organizations choose you and why. [00:14:38] Vince Menzione: Yes, exactly. Exactly. So how do you get them to show up in that way? [00:14:43] Vince Menzione: Like especially if they’re like, how do you coach them through that? ’cause it feels like it’s still exists, right? This like mentality or this mindset. I can do all things, especially with the shiny objects that we’re facing today. [00:14:55] Rebecca Jones: Mm-hmm. [00:14:55] Vince Menzione: And I feel like we’re almost, I, I almost feel like we’re at a point right now where we were getting clearer and we’ve had so many shiny objects, even just in the last few months. [00:15:03] Vince Menzione: Like you were talking about how like months feels like ears, uh, you know, I’ll, I’ll use the Claude example here. Yeah. ’cause we, a lot of us pivoted and shifted and like, what do I do now as a partner in the room? Again, I think you, you mentioned the solving for business outcomes for client outcomes as opposed to chasing the next shiny object. [00:15:24] Vince Menzione: Like how do you get, how do you coach them on that? [00:15:27] Mark Yaphe: It’s always on the agenda. It’s, it’s day one conversations. Yeah. Who are you? What’s unique about you? How do you deliver value? Which customers do you focus on and with? Which use cases, and if it is a jack of all trades. Then my team, my and my team will help ’em. [00:15:42] Mark Yaphe: We know that down to specific areas of focus. [00:15:44] Vince Menzione: Yeah. So how do partners need to evolve their capabilities? Like how do they, I mean, how do they actually hone in on this? Like, you know, okay, I can state one thing, but how do I hone in on my capabilities, offerings and teams to stay relevant during this time? [00:15:59] Mark Yaphe: Um, what I’m coaching them on right now? Yeah. That’s what I is, uh, use the technology internally. The agentic tools and the gen AI tools are. I’ve been at this for a while, and the tools that exist right now dramatically expand your capability and capacity. So the thing I coach ’em is embed them in your organization. [00:16:18] Mark Yaphe: Yeah. Mm-hmm. Tackle those key things organizationally. You need to change and leverage these tools to help you accelerate. [00:16:23] Vince Menzione: And they’ll help you solve, they’ll help you solve for absolutely any of them. Right. It’s like, it’s like hiring a consulting organization to come in and solve for that. [00:16:29] Mark Yaphe: Yeah. [00:16:29] Vince Menzione: Yeah. How are you thinking through this? [00:16:31] Rebecca Jones: Well, uh, there’s a couple things I’m thinking about. Um, if you start to. I’ll stay with the customer for just a minute because you’re talking about Claude and just the dramatic improvement. [00:16:45] Guest: Yeah, [00:16:46] Rebecca Jones: that’s there. Just with Claude, uh, we start to think about highest and best use of the model because, uh, we had another talk earlier about the economic conditions and the. [00:16:58] Rebecca Jones: And so now we’re asking partners like, right, [00:17:01] Vince Menzione: the tokens. [00:17:01] Rebecca Jones: Yeah. Yep. How do you specialize and be focused by industry, by workflow, by use cases, you’re gonna start to look at what is the ROI of that investment? Is this a good enough? Look at the models, look at how you’re using that, and you’re having a token conversation because the economics might not be there. [00:17:21] Rebecca Jones: And so as you’re a business and a customer looking to transform their organization. They’re going to look across the business and figure out what are the highest and best use cases that should get that focus. And as a partner, if you wanna be in that conversation and really helping that company or that. [00:17:40] Rebecca Jones: Customer transform from where they are. It’s not only industry specialization, but it’s functional and workflow and really helping them understand what they should be using in that particular use case. So specialization is king or queen and that, um, scenario, and that’s where, you know, you ask partners today to specialize because there’s a whole economic conversation coming behind that, around how do you think about the models as that new one shows up? [00:18:09] Vince Menzione: Let’s shift from the technical side to the human side. [00:18:12] Rebecca Jones: Yeah. [00:18:13] Vince Menzione: Super important, right? I mean, we were having this conversation internally, like everybody’s saying, you know, jobs are going away, jobs are going away. I think I, I believe more jobs are gonna happen, but we’ve gotta get humans aligned properly to what their new roles will be. [00:18:29] Vince Menzione: Comments on this one? [00:18:31] Mark Yaphe: I think this is like a classic organizational transformation Yeah. Question. Mm-hmm. Where the 70, 80% of the problems are people process change. Um, I, I think there are these three areas that organizations need to focus on, and I’m gonna sound a little bit repetitive, but one, it’s okay. [00:18:46] Mark Yaphe: It’s, uh, the role of the team members have gotta be focused on outcomes, especially when things are moving quickly and there’s ambiguity. The one way that you can anchor on moving in the right direction is how do I let my customer, so one is outcomes. The second one is the builder mindset. Move from, I’m presenting, I’m hearing, but I’m gonna build things. [00:19:05] Vince Menzione: Yeah. [00:19:05] Mark Yaphe: And the last one is, uh, inspiring your team, making them competent and confident to navigate ambiguity because that is the premise upon which everybody’s operating. So those three, [00:19:17] Vince Menzione: Rebecca, what capabilities. Would be embodied in, in that organization that Mark describes. [00:19:23] Rebecca Jones: Yeah, I think that the growth mindset, you know, if you can package that around, you can either, um, think about being disrupted or being a disruptor. [00:19:34] Rebecca Jones: And if you have a growth mindset around the opportunity that’s ahead, it’s a whole different perspective of the challenges before you. I love that. And so when I think about what. Capabilities. You know, it’s the critical thinking and the judgment, human connection. We’re all here for a reason. Yes. Right? [00:19:50] Rebecca Jones: Yes, yes. And so as a leader, um, really helping set that tone and letting them see the art of the possible, um, around that vision. But it’s really, if I boiled it down to one thing, it’s having a growth mindset to the opportunity ahead. [00:20:05] Vince Menzione: Well, I wanna open it up. We have about five minutes left. Yeah. And this has been so insightful, but I. [00:20:11] Vince Menzione: I mean, I feel the energy. There’s gotta be some questions out here too. ’cause this, we have two incredible experts up here talking. I mean, and this is such an impactful conversation today. So John’s got a mic and uh, I think we’ve got some questions coming. [00:20:32] Vince Menzione: Yeah, [00:20:33] Rebecca Jones: this’s [00:20:33] Vince Menzione: a long way [00:20:33] Rebecca Jones: around. [00:20:34] Vince Menzione: Took a [00:20:34] Guest: thanks, long David Younger with. Thank you. That was great, great discussion. So, uh, you, you brought up a key statistic, uh, which is the MIT data and around the, the 90, I think it was 95%. Of, uh, businesses, uh, are not in production. And, and actually they, they went further to say that 95% of businesses. [00:20:56] Guest: Uh, we’re achieving zero ROI. And, and that was about a year ago, right? And now, and now you said the number, I think the number was quoted earlier today too, is, is shifting to about 70% of those, uh, projects in production. I’m curious to, to know as you, and I think you nailed it too, when you talk about product, right, have a product mindset or business mindset, right? [00:21:16] Guest: Not just how can I save money, but how can I actually generate revenue, whether it’s saving money or generating revenue. Where would you say. Uh, what, what percentage of companies you talk to are actually achieving real ROI would you say? [00:21:31] Rebecca Jones: Yeah, that’s a, that’s a great question. Really. Great. So I’ll go back and explain a little bit more about what I mean by product mindset. [00:21:39] Rebecca Jones: So a lot of companies did get stuck or there were just, uh, a. Large amount of pilots happening in the organization. And that’s not a bad thing. ’cause you think about, that’s a builder mindset, go and test and trial. But when you’re starting to look at true business transformation, you really need to think about where that, um, high value use case is. [00:22:00] Rebecca Jones: So a. The product mindset I’m talking about is taking a long-term view of the outcomes you’re trying to achieve and how are you going to measure those? And then look at that workflow, that function, and if you’re an expert in that function, whether that be a sales process or a marketing process, you know what KPIs your business is trying to drive today, and you start to unpack that. [00:22:24] Rebecca Jones: And so we’ve seen and what. Um, the most, uh, accelerated motion is knowing the KPIs and the measures you’re trying to achieve and then working towards that. And from there you can build, right? And you start to think and you have an ecosystem approach to that workflow or work stream. So we have seen, um, everybody wants cost on the system. [00:22:46] Rebecca Jones: Um, we have seen dramatic cost reduction in areas we’ve seen, you know. Two to three times, um, faster time to market. Um, there’s multiple things that we’ve seen as, uh, leaders really start to unpack that, understand what they’re trying to accomplish in the business, and I’m happy to go into greater detail. [00:23:06] Rebecca Jones: I know we have just a couple minutes left, but that’s just the product mindset up. How do you get started and how do you look at that long-term opportunity? [00:23:15] Vince Menzione: Really great answer. Mark, do you wanna add that? [00:23:17] Mark Yaphe: I think if you look at all use cases. Maybe 30% perform. But if you look at this across enterprise, I think each enterprise is finding very specific use cases where they’re driving ROI and and um, and so I think it’s about picking your spots, knowing who you are, identifying the top priority ones, not worrying about the broad enterprise transformation. [00:23:38] Mark Yaphe: Find those areas where you can drive value a little bit. Yeah, [00:23:41] Vince Menzione: that’s great that that’s almost a mic drop moment in my opinion. Yeah. That’s really great. Any other questions? I we’re holding every, oh, we got one in the back. I was gonna say I’m holding people up from happy hour. Yeah, [00:23:53] Rebecca Jones: just, we’ll just bring the cocktails in here [00:23:56] Vince Menzione: pretty soon. [00:23:57] Guest: Uh, Jeremy with Integral, um, um, a money question, something comparable. Uh, activator portfolio, the programs for founder firms that are trying to really get off the ground with new ideas. And there’s some comparable programs, I think with different providers. How much of that is a strategy, and I don’t wanna put you on the spot if activating portfolio aren’t the things you’re covering, but, but that money investment for startups that are trying to grow and really focus on AWS uh, the thousand dollars is the founder version that gets us in and then a hundred thousand dollars. [00:24:26] Guest: It’s a bit difficult to get into. And then there’s bigger ones after that if we attend the schools and all these things. But I’m thinking about as we all are trying to grow and really focus in AWS, which a lot of folks really wanna do with Bedrock and all the things that are kind of cool going on, it’s just. [00:24:40] Guest: Great AI focused conversation, but how is that playing into attracting more of the MSPs that are, that are trying to grow and more of the startups to really funding this idea of, of startup mentality. Hopefully that’s not too off topic, but your, your fair game [00:24:57] Mark Yaphe: was, was the question, how does funding. [00:25:01] Mark Yaphe: Attract startups in specific categories, process. [00:25:04] Guest: I think it’s, it’s about if there’s, uh, the other hyperscalers also have programs comparable. So Microsoft’s program is, uh, 150 grand to to, to build out the founder kind of, and it’s fairly easy to get into. Aw. WS is a bit harder to get into, but is that going to change as far as using that as a, as a key strategy for incubating more and more ideas to accelerate the velocity of everything you guys were talking about? [00:25:25] Mark Yaphe: I’m really not the right person. Definitely outta my wheelhouse on that. No problem. [00:25:31] Guest: Yeah. [00:25:37] Vince Menzione: And we’re about seven seconds away from uh, happy hour. [00:25:41] Rebecca Jones: I know, [00:25:41] Vince Menzione: I know. This was fantastic. I know. It was so great. [00:25:44] Rebecca Jones: Yes. [00:25:45] Vince Menzione: And I think the McKenzie thing is gonna stick. I think it is, it is. [00:25:48] Rebecca Jones: Now, mark, I’m gonna make [00:25:49] Vince Menzione: sure it does. And Mark, it was great to have you up on stage with us today. So, so great to have AWS supporting us and sponsoring the event with us and, uh, and having just this broad audience of people just so interested in. [00:26:02] Vince Menzione: Being in the room and and learning from each of you. So thank you so much today. Thank you. Appreciate it. Thank you. Thank you. [00:26:09] Mark Yaphe: Thanks for listening to The Ultimate Partner [00:26:11] Vince Menzione: Podcast. If today’s conversation resonated, share it with a partner leader in your network. Subscribe where you listen, and head over to the ultimate partner.com. [00:26:22] Vince Menzione: For show notes related content and the resources for this episode. And if you haven’t already, now’s the time to register for the Ultimate Partner Live Event in Reston, Virginia, October 26th through October 28th. Until next time, keep showing up in the rooms that matter because being in the room changes everything.

AWS Morning Brief for the week of September 14th with Corey Quinn. Links:Amazon API Gateway now supports 1 MB execution logs with configurable delivery destinationsAmazon S3 Object Lock now supports variable retention with event holdsLambda's slow-motion reinvention of EC2Amazon EC2 now supports specifying compatible instance types on AMIsAnnouncing second-generation single-rack AWS OutpostsHow AWS thinks about FinOps Automation and TrustIntroducing Amazon EBS Volume Clones across AWS accountsHow to migrate from Amazon CloudSearch to Amazon OpenSearch ServerlessIntroducing Pizza Bot, an open source inbox for AI agents that work in the backgroundThree consecutive CVEs, all AWS-authored code

In this episode of Shift AI, Praerit Garg, CEO of One Identity, joins host Boaz Ashkenazy for a wide-ranging conversation on what happens to enterprise security when AI agents start outnumbering the humans they work alongside.Praerit has spent his career on both sides of this problem, from building Active Directory at Microsoft to running identity at AWS, and he says the thing keeping him up at night isn't a new category of threat at all. It's an old one moving at a speed nobody has built the guardrails for yet, and he points to a very recent, very public example of exactly how fast it can get away from you.This one's for CISOs, CTOs, platform and security engineers, and any founder scaling a company that's already handing real work to autonomous agents.Recorded Live at Baker Tily during Seattle Tech Week 2026. Thank you to Stifel Bank and Wison Sonsini for sponsoring.Chapters[00:00] Welcome back — PG's journey from Smartsheet to CEO of One Identity[01:58] What One Identity does: identity governance, explained[03:41] How the firewall evaporated and identity became the new perimeter[04:24] Rethinking identity for a world full of AI agents[07:14] Why agent identities are harder to secure than human ones[08:00] Breaking down the OpenAI and Hugging Face agent escape[09:03] Least privilege: the hardest idea in security to actually pull off[11:19] What keeps PG up at night as agents start to outnumber people[15:19] Sovereign AI, air-gapped models, and the return of on-prem[18:18] Scaling Smartsheet fast, and why flexibility beats architecture bets[20:20] What CEOs should be asking security vendors and usually aren't[22:37] The next five years: agents outnumbering humans and AI writing the codeConnect with Praerit GargLinkedIn: https://www.linkedin.com/in/praerit-garg/Company: One Identity (oneidentity.com)Connect with Boaz AshkenazyLinkedIn: https://www.linkedin.com/in/boazashkenazy/Email: info@shiftai.fm

Herzschrittmacher, Zahnimplantate, OP-Roboter oder Diagnose-Software: Kaum eine Branche greift so tief in unser Leben ein – und kaum ein Markt ist so streng reguliert wie die Medizintechnik. Allein in Europa müssen Hersteller Hunderte von sich ständig ändernden Regelwerken befolgen, um ihre Produkte auf den Markt zu bringen und dort zu halten. In dieser Folge von Digitale Vorreiter:innen spricht Host Christoph Burseg mit Markus Müller, Co-Founder von Flinn AI. Markus hat es sich mit seinem Team zur Aufgabe gemacht, das „AWS für die Medizintechnik“ zu bauen. Mit spezialisierten KI-Lösungen hilft das Wiener Start-up Herstellern dabei, komplexe Compliance-Prozesse, Literaturanalysen und Beschwerdemanagement drastisch zu vereinfachen und zu automatisieren. In dieser Episode erfährst du: People First & Shared Purpose: Warum Markus zuerst das ideale Gründer-Team zusammengestellt hat, bevor er überhaupt die Geschäftsidee definierte Die Hürden der MedTech-Regulatorik: Warum europäische Vorgaben für Hersteller extrem komplex sind KI als Compliance-Booster: Wie Flinn AI medizinische Studien und Gesetzestexte analysiert und wo KI den Menschen überlegen ist Validieren ohne zu bauen: Wie das Team die erste Finanzierungsrunde mit Klick-Prototypen und Absichtserklärungen abschloss – und warum der Bau eines Produkts oft der teuerste Weg ist, eine Idee zu testen US-Expansion & Enterprise-Fokus: Warum sich Flinn AI bewusst auf die größten MedTech-Konzerne der Welt konzentriert und welche Unterschiede zwischen dem europäischen und dem US-Markt bestehen

Special guest, Simon Hollander is Senior Corporate Counsel at Amazon Web Services and supports Products and Security Legal across Asia Pacific as AWS's regulatory expert on cloud and AI. Simon shares his interesting career path and the women lawyers who influenced every pivotal career decision he ever made. We hear about the tools coming out of leading AI models, Simon's insights on brain fry, and what lawyers should be working on in this age of AI.If you enjoyed this episode and it inspired you in some way, we'd love to hear about it and know your biggest takeaway. Head over to Apple Podcasts to leave a review and we'd love it if you would leave us a message here!In this episode you'll hear:How nearly every pivotal legal career decision Simon has ever made was influenced by a woman lawyer. Listen in for some shoutouts to our LOA community!The “uncommon sense” lesson lawyers need to learn that no law school teachesSimon's experience from the front line of AI development and the “brain fry” phenomenon replacing “brain rot”About SimonSimon is Senior Corporate Counsel at Amazon Web Services and supports Products and Security Legal across Asia Pacific (ex-China but including Japan and New Zealand). Before joining Amazon Web Services in 2016, he was Senior Counsel at Accenture Japan. Before going in house he was in private practice on the corporate legal team at Morrison & Foerster LLP in Tokyo. He is qualified as a barrister in New Zealand and has a BA/LLB from Auckland UniversityBefore life as a lawyer Simon spent seven years working as an IT Consultant for Deloitte Tohmatsu, and later as an environmental policy consultant at Tokio Marine Risk Consulting before deciding to earn his New Zealand bar admission while living and working in Japan and to finally try out becoming a lawyer. Simon grew up - in his own words - an army brat, moving around attending 16 schools. He moved to Japan straight out of uni and has lived here for 27 years now. In his years in Japan he has been a rugby referee, managed the local French rugby club for several years, been a club DJ and his latest passion is running and is hoping he can run the Tokyo Marathon once again with the current lottery. In his free time he also has a video blog about weekly news and culture topics in Japan he has been doing for more than 15 years now.Like everyone else Simon is wrapped up in learning AI and feels very lucky to be in a position to get access to the latest models and tools, and is a trainer of how to use this tech inside Amazon Legal globally, and has given seminars for regulators inside and outside of Japan on the technology. Connect with SimonLinkedIn https://www.linkedin.com/in/simon-hollander-9b5a3a5/  LinksPunk Doily: https://www.instagram.com/punkdoily Connect with Catherine LinkedIn https://www.linkedin.com/in/oconnellcatherine/Instagram: https://www.instagram.com/lawyeronair

A Rust Framework to Simplify Distributed Systems Building software that runs across many machines is notoriously difficult. Developers have to grapple with problems such as race conditions, partial failures, and message ordering. Notably, one category of distributed software has largely escaped these burdens. A distributed database can spread a single query across thousands of machines, handling the coordination, failure recovery, and ordering internally. This raises a natural question of why general-purpose distributed programming can’t feel the same way. This is a highly practical problem at AWS, because the reliability of cloud infrastructure depends on getting distributed systems right at massive scale. Joe Hellerstein spent thirty years as a database and distributed systems researcher at UC Berkeley, where he pioneered much of the foundational thinking on applying database ideas to distributed programming. He is now at AWS, where he works to bring his research into production through Hydro, which is a Rust framework to bring declarative queries to general-purpose distributed programming. In this episode, Joe joins Sean Falconer to discuss how ideas from the database world could make distributed programming dramatically simpler and safer.Sponsorship inquiries:sponsor@softwareengineeringdaily.com The post A Rust Framework to Simplify Distributed Systems appeared first on Software Engineering Daily.

AWS VP of Global Networking Matt Rehder joins Corey Quinn to pull back the curtain on the massive network infrastructure behind AWS. They explore resiliency at scale, AWS's move toward flatter networks, the advantages of building custom hardware, and why AI is making networking exciting again.Show Highlights: (01:08) Meet AWS Networking Lead(02:01) Why AWS Avoids Global Outages(05:23) RNG Flat Network Explained(10:08) Overbuild Capacity And Custom Hardware(17:37) VPC Virtual Network Origins(19:50) Why TCP Still Wins(20:38) SRD Inside AWS(21:54) Opt In SRD Transport(25:31) Networks As Utilities (27:24) Learning And Growing Engineers(29:22) Training Talent In House(31:27) AI Rekindles Networking(34:26) Where To Learn Networking

A Rust Framework to Simplify Distributed Systems Building software that runs across many machines is notoriously difficult. Developers have to grapple with problems such as race conditions, partial failures, and message ordering. Notably, one category of distributed software has largely escaped these burdens. A distributed database can spread a single query across thousands of machines, handling the coordination, failure recovery, and ordering internally. This raises a natural question of why general-purpose distributed programming can’t feel the same way. This is a highly practical problem at AWS, because the reliability of cloud infrastructure depends on getting distributed systems right at massive scale. Joe Hellerstein spent thirty years as a database and distributed systems researcher at UC Berkeley, where he pioneered much of the foundational thinking on applying database ideas to distributed programming. He is now at AWS, where he works to bring his research into production through Hydro, which is a Rust framework to bring declarative queries to general-purpose distributed programming. In this episode, Joe joins Sean Falconer to discuss how ideas from the database world could make distributed programming dramatically simpler and safer.Sponsorship inquiries:sponsor@softwareengineeringdaily.com The post A Rust Framework to Simplify Distributed Systems appeared first on Software Engineering Daily.

In this episode of The Joe Reis Show, I catch up with my good friend Christophe Blefari, co-founder of NAO, to dig into what's actually happening on the front lines of AI agents and data engineering. We talk about the evolution from building SQL IDEs to agentic analytics harnesses, how prompt-driven workflows are reshaping data teams, and why age-old problems like data discovery, modeling, and documentation are suddenly roaring back. We also dive into the risks of "token slop," whether data and software engineering roles are destined to merge, Christophe's take on DuckDB's acquisition by AWS, and the realities of building AI tools across Europe and the US.Nao: https://getnao.io/

A Rust Framework to Simplify Distributed Systems Building software that runs across many machines is notoriously difficult. Developers have to grapple with problems such as race conditions, partial failures, and message ordering. Notably, one category of distributed software has largely escaped these burdens. A distributed database can spread a single query across thousands of machines, handling the coordination, failure recovery, and ordering internally. This raises a natural question of why general-purpose distributed programming can’t feel the same way. This is a highly practical problem at AWS, because the reliability of cloud infrastructure depends on getting distributed systems right at massive scale. Joe Hellerstein spent thirty years as a database and distributed systems researcher at UC Berkeley, where he pioneered much of the foundational thinking on applying database ideas to distributed programming. He is now at AWS, where he works to bring his research into production through Hydro, which is a Rust framework to bring declarative queries to general-purpose distributed programming. In this episode, Joe joins Sean Falconer to discuss how ideas from the database world could make distributed programming dramatically simpler and safer.Sponsorship inquiries:sponsor@softwareengineeringdaily.com The post A Rust Framework to Simplify Distributed Systems appeared first on Software Engineering Daily.

A Rust Framework to Simplify Distributed Systems Building software that runs across many machines is notoriously difficult. Developers have to grapple with problems such as race conditions, partial failures, and message ordering. Notably, one category of distributed software has largely escaped these burdens. A distributed database can spread a single query across thousands of machines, handling the coordination, failure recovery, and ordering internally. This raises a natural question of why general-purpose distributed programming can’t feel the same way. This is a highly practical problem at AWS, because the reliability of cloud infrastructure depends on getting distributed systems right at massive scale. Joe Hellerstein spent thirty years as a database and distributed systems researcher at UC Berkeley, where he pioneered much of the foundational thinking on applying database ideas to distributed programming. He is now at AWS, where he works to bring his research into production through Hydro, which is a Rust framework to bring declarative queries to general-purpose distributed programming. In this episode, Joe joins Sean Falconer to discuss how ideas from the database world could make distributed programming dramatically simpler and safer.Sponsorship inquiries:sponsor@softwareengineeringdaily.com The post A Rust Framework to Simplify Distributed Systems appeared first on Software Engineering Daily.

A Rust Framework to Simplify Distributed Systems Building software that runs across many machines is notoriously difficult. Developers have to grapple with problems such as race conditions, partial failures, and message ordering. Notably, one category of distributed software has largely escaped these burdens. A distributed database can spread a single query across thousands of machines, handling the coordination, failure recovery, and ordering internally. This raises a natural question of why general-purpose distributed programming can’t feel the same way. This is a highly practical problem at AWS, because the reliability of cloud infrastructure depends on getting distributed systems right at massive scale. Joe Hellerstein spent thirty years as a database and distributed systems researcher at UC Berkeley, where he pioneered much of the foundational thinking on applying database ideas to distributed programming. He is now at AWS, where he works to bring his research into production through Hydro, which is a Rust framework to bring declarative queries to general-purpose distributed programming. In this episode, Joe joins Sean Falconer to discuss how ideas from the database world could make distributed programming dramatically simpler and safer.Sponsorship inquiries:sponsor@softwareengineeringdaily.com The post A Rust Framework to Simplify Distributed Systems appeared first on Software Engineering Daily.

In this episode of the industry's shiniest five-year-old podcast, Robert Lenzhofer discusses the innovative Hizi platform, a self-service operating system for iGaming studios that simplifies game development, deployment, and management, aiming to revolutionize the industry with cloud-based solutions. Hosts Fintan Costello and Jon Bruford welcome Robert – a returning guest! – as they discuss the usual mish-mash of topics alongside Robert's innovation.As ever, we thank our superb sponsors – you can find out more about Optimove, World Gaming, and GLI further down this page…Choice quotes: "This is more like an operating system for studios""Allows you to create any RNG game directly in the back office""It's like AWS for the gambling industry"“The RGS all grown up. The operating system for studios.”“If you still have to code into the backend, then it's not self-service.”“We just give you the best tool that possibly can be built.”Chapters (but add 30 seconds or so because of our beautiful music, which is copyright Mara Carlyle…)00:00 - Opening banter and the challenge of recording multiple episodes 01:02 - Moving house, lampshades, and the magnetic knife rack 03:18 - Holiday talk, hustle culture, and the death of downtime 04:04 - The world's best theme park in Devon: Diggerland, and possibly the best jingle for a theme park ever. 10:29 - Robert's summer chaos and building a point-and-click adventure with his daughter 12:20 - Introducing Robert Lenzhofer and the move beyond Holle Games 13:01 - What Hizi means and why it is about more than an RGS 14:43 - What the platform is for in practical studio terms 15:48 - Why RGS infrastructure should be treated like a commodity 16:29 - Self-service signup and instant dedicated instances 18:14 - Pricing tiers and what's included in the basic package 19:20 - The no-code, AI-assisted Hizi engine 21:02 - Early traction, partner growth, and game deployments 23:36 - What studios actually do inside the platform 24:34 - Why billing and back-office tooling matter for small teams 26:15 - Migration paths for existing studios and hybrid deployments 27:40 - How Hizi compares with Stake's model and game-upload systems 29:00 - The “end of RGS” idea and B2C engine support 31:12 - Could a simple card game or pub machine be built on Hizi? 33:15 - How the platform reduces startup friction and contract pain 35:07 - What onboarding looks like and the learning curve 36:06 - Why Hizi's challenge is broader than a single-operator system 37:43 - Scaling with a lean team and moving from beta to wider onboarding 41:39 - Distribution as the bottleneck for smaller studios 44:05 - Starting a game studio and the “Doctor Hour” joke 45:16 - Bamboo Guerillas arrives 47:56 - Closing thanks and an invitation to revisit the project in 12 monthsRobert on LinkedIn: https://www.linkedin.com/in/robertlenzhofer/Resources & Links:As ever, we thank all of our sponsors for their vibrant and excellent support that makes all of this… magic… possible.Optimove, who turn customer data into something special, with tools that make businesses just plain work better. Optimove, your support helps us to keep creating content for an industry that probably thinks we disappeared years ago.Then of course there is Clarion Gaming, no hang on World Gaming, providers of the magnificent ICE expo and iGB Live! in London. There is simply nobody better at what they do.And the new-ish-est members of the family, the excellent Gaming Laboratories International. GLI is a world-class Testing, Inspections and Certification company committed to delivering the highest quality land-based, lottery, and iGaming testing and assessment services, working in more than 710 jurisdictions.For more information, visit gaminglabs.com.The Gambling Files podcast delves into the business side of the betting world. Each week, join Jon Bruford and Fintan Costello as they discuss current hot topics with world-leading gambling experts.Website: https://www.thegamblingfiles.com/Subscribe on Apple Podcasts: https://apple.co/3A57jkRSubscribe on Spotify: https://spoti.fi/4cs6ReF Subscribe on YouTube: https://www.youtube.com/@TheGamblingFilesPodcast Fintan Costello on LinkedIn: https://www.linkedin.com/in/fintancostello/ Jon Bruford on LinkedIn: https://www.linkedin.com/in/jon-bruford-84346636/ Follow the podcast on LinkedIn: https://www.linkedin.com/company/the-gambling-files-podcast/ Sponsorship enquiries: https://www.thegamblingfiles.com/contact/ Get our newsletter: https://thegamblingfilestldr.substack.com/

What should a student know before walking into welding school on day one? In this episode of Weld Wednesday with AWS, I sit down with Josh Wolfe, welding instructor at Laurel Oaks in Wilmington, Ohio, and host of the Speaking of Skilled Trades podcast, for an honest conversation about what it really takes to succeed in welding education. We talk about why safety rules in a welding lab are different from the arbitrary rules students may be used to, how quickly one careless decision can change a life, and why PPE and safe habits have to become automatic. Josh and I also discuss the importance of attitude, grit, accepting direct feedback, and using every available minute in the booth. Nobody looks back and wishes they had burned less rod. For more information on AWS Click Here Josh Wolfe on Instagram: @wolfe_cte Speaking of Skilled Trades podcast: Listen on Spotify Arc Junkies Podcast: arcjunkies.com Weld Wednesday with AWS: aws.org/podcasts Arc Junkies Instagram: @ArcJunkiesPodcast

Are you on social media? Of course you are. So follow us! Twitter: @MemberTheGameInstagram: @MemberTheGameTwitch.tv/MemberTheGame⁠Youtube.com/RememberTheGame⁠⁠Facebook.com/RememberTheGamePodcast⁠⁠TikTok.com/@MemberTheGame⁠And if you want access to hundreds of bonus (ad-free) podcasts, along with multiple new shows EVERY WEEK, consider showing us some love over at Patreon. Subscriptions start at just $3/month, and 5% of our patreon income every month will be donated to our 24 hour Extra-Life charity stream at the end of the year!⁠Patreon.com/RememberTheGame⁠Find Andre C at :X & Bluesky @thatcanadaguyInstagram & Threads @thatcanadadudeCatch Andre doing the Pop Spot with his co-host AWS as they review all the wrestling shows that they attand at https://www.youtube.com/@BackbreakerVideoCatch the return of Backbreaker Pro Wrestling right after Dynamite on April 22 at https://www.Twitch.tv/miketherefCheck Andre out Every Thursday evening for Marvel Talk and Sunday Morning for Point of View over at https://www.Youtube.com/@OurLocalEstablishment or https://www.twitch.tv/OurLocalEstablishmentI know, I know. This game isn't "retro". But it's almost 10 years old, the new season of South Park is right around the corner, and quite frankly, it's an awesome game. This week we're talking South Park: The Fractured But Whole.This one's a sequel to (the also phenomenal) Stick of Truth. Instead of classic turn-based RPG combat, it's a tactical game. Instead of Lord of the Rings, the kids are playing superheroes. Both games are hilarious and like playing a season of the show. If you're a South Park fan, these are 100% must-plays.The Human Kite to my Professor Chaos, my buddy Andre, is my guest this week. We had a great time breaking down all the superhero alter egos and laughing at the easter eggs in this one. A lot of spoilers, but if you haven't played these, I hope this episode convinces you to get off your wallet. You get to fight red wine drunk Randy for fuck sakes.And before we head on down to South Park, I put together another edition of the Infamous Intro!This week someone asks how I write my podcast notes, we talk about Star Wars Zero Company, and is it cheating to use a walkthrough??Plus we play another round of 'Play One, Remake One, Erase One', too! This one features 3 retro South Park games: South Park (N64/PS1), Chef's Luv Shack, and South Park Rally.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

How can network architects successfully manage 95,000 hosts while navigating the complexities of large-scale cloud migrations? Devender Singh, a Principal Cloud Architect, joins Ned and Kyler to discuss the practical realities of managing network chaos, the migration from Transit Gateways to AWS Cloud WAN, and strategies for addressing the technical debt often encountered during enterprise... Read more »

How can network architects successfully manage 95,000 hosts while navigating the complexities of large-scale cloud migrations? Devender Singh, a Principal Cloud Architect, joins Ned and Kyler to discuss the practical realities of managing network chaos, the migration from Transit Gateways to AWS Cloud WAN, and strategies for addressing the technical debt often encountered during enterprise... Read more »

How can network architects successfully manage 95,000 hosts while navigating the complexities of large-scale cloud migrations? Devender Singh, a Principal Cloud Architect, joins Ned and Kyler to discuss the practical realities of managing network chaos, the migration from Transit Gateways to AWS Cloud WAN, and strategies for addressing the technical debt often encountered during enterprise... Read more »

AWS Morning Brief for the week of September 8th with Corey Quinn. Links:AWS Lambda now supports SnapStart for container image functionsAmazon CloudWatch now supports warm-up periods for alarmsAmazon Kinesis Data Streams announces data delivery to general purpose Amazon S3 bucketsAmazon Linux 2027 is now available in public previewAmazon CloudFront announces API support for flat-rate pricing plansAAA games on a $35 stick: How Luna removes the hardware barrier with AWSHow t54 built a trust layer with Amazon Bedrock AgentCore paymentsIntroducing Claude Fable 5.1 on AWSTokenomics at scale: How Jamf built real-time spend enforcement for Amazon BedrockHow PGA TOUR automated live profanity detection with AWS using Amazon TranscribeAWS and Microsoft Azure collaborate to expand multicloud networkingWe invited a direct competitor into Security Hub Extended. Here's why.Detect stalled Amazon S3 live replication to prevent unexpected storage costsSix AWS security bulletins in five days

In this episode, Ray Cochrane records from the Michigan studio on the one year anniversary of losing the show’s original host, Todd Cochrane. The featured story is Anthropic’s $5 million grant program, which pays outside researchers to measure whether AI is actually good for the people using it. Ray also covers Anthropic’s Enterprise Frontier Safeguards, Google’s Fairwind cyber defense program, Meta’s organizational second brain, sixteen green AI projects across Asia-Pacific, an Oklahoma Bitcoin mine condemned after leaking 3.8 million gallons of water, BepiColombo closing in on Mercury, and the 2026 Ig Nobel Prizes. – Want to start a podcast? Its easy to get started! Sign-up at Blubrry – Thinking of buying a Starlink? Use my link to support the show. Subscribe to the Newsletter. Email Ray if you want to get in touch! Like and Follow Geek News Central’s Facebook Page. Support my Show Sponsor: Best Godaddy Promo Codes Get 1Password Full Summary Cochrane opens from the studio in Michigan, recording on the one year anniversary of the show losing its original host, Todd Cochrane, his father. The family has gathered for the occasion. He also plans to record several episodes throughout the week as a commemorative run, so listeners should expect a heavier release schedule than usual. He also shares where things stand. He and Delaney have gone back and forth on relocating to Michigan, but the family is pushing, and the plan is firming up for the coming month or so. Part of the draw is getting his dad’s studio cleaned up and running the way it used to. Finally, he passes along an update on the Zuvers, a story long-time listeners will recognize. The father of the three children is due out of jail soon, though he now faces retrial for the murder of the three boys. Cochrane notes that the original prison term related to their return rather than the murders themselves. The family’s expectation, he says, is that this time the sentence will be permanent. Anthropic Puts $5 Million Behind Measuring AI’s Effect on You The featured story asks a question the industry has mostly avoided. Not whether a model is smart, but whether you are better off after using it. Anthropic is funding independent research to find out, and the structure is the interesting part. The money creates what the field calls evaluations: standardized tests for AI models. Hundreds already exist for coding, math, and reasoning. However, almost none measure whether the tool is good for the human on the other end. Crucially, Anthropic is not building these tests in-house. Grantees receive funding, model access and technical support, then work fully independently. Everything they produce must be published open source, so any developer at any company can run it. As Cochrane puts it, Anthropic is paying to create a ruler other people will use to measure Anthropic. The example Anthropic leads with is deliberately uncomfortable. Claude might offer diet and workout advice to someone asking about weight loss. But if that user has a history of disordered eating, the same response becomes actively harmful. Cochrane connects this to sycophancy, a topic the show has returned to before, and notes that models carry no real memory of who you are unless you tell them. That is exactly why the problem has gone unmeasured. Code compiles or it doesn’t. Math checks out or it doesn’t. Wellbeing has no answer key, because the identical response can help one person and harm the next. The Five Things Anthropic Wants These Tests to Do Cochrane walks through all five criteria, since each targets a specific way this research usually fails. First, state plainly what you are measuring. It is easy to measure something adjacent, such as how often a model uses warm language, then publish numbers about a proxy while claiming insight into loneliness itself. Second, involve clinicians and subject-matter experts in designing and validating the tests. A capable engineer may simply not know what the warning signs of an eating disorder look like in text. Without those people in the room, the test measures what engineers imagine the harm looks like. Third, count overcompliance and overrefusal as harms. Overcompliance is the obvious failure. Overrefusal is the model becoming so cautious it turns useless, or shutting down someone who had nowhere else to ask. Cochrane adds that overrefusal is far harder to spot, because you often cannot tell it is degrading until it has degraded. Fourth, reflect real multi-turn usage. Most safety testing throws one nasty question at a model and checks for refusal. Meanwhile, actual harm builds across a long conversation where every individual message reads as fine. Fifth, validate the automated graders against real experts. Scoring thousands of conversations means an AI grades the AI. Consequently, a subtly wrong grader skews every downstream number in the same direction, and nothing in the process flags it. Cochrane expects this to be the hardest criterion to satisfy, since psychiatric and medical specialists do not come cheap by the hour. Applications close September 21st, and shortlisted applicants will be notified by October 5th. Notably, the announcement names no individual researcher or executive. Sponsor: GoDaddy Economy hosting $6.99/month, WordPress hosting $12.99/month, domains $11.99. Website builder trial available. Use codes at geeknewscentral.com/godaddy to support the show. Anthropic’s Enterprise Frontier Safeguards Keep Your Logs in Your Vault Anthropic’s second announcement targets a completely different audience. Catching misuse across many sessions requires keeping logs. However, banks and hospitals cannot hand that data to an outside vendor, because regulators will not allow it. Safety monitoring and compliance were in direct conflict. The fix moves where the data lives. Activity logs go into the customer’s own cloud bucket at Amazon, Microsoft or Google, locked with keys the customer controls. Automated systems scan a rolling window for serious abuse such as credential theft, and alerts route straight to the customer’s own security team. No human at Anthropic reads it, and Anthropic does not charge for the feature. The backstory explains the urgency. Anthropic had begun retaining thirty days of data with its Fable 5 model, specifically to catch patterns that only appear across multiple sessions. Regulated customers had to walk away immediately. Over a hundred organizations helped shape the result, including a quarter of the Fortune 100 and every US globally systemically important bank. It works across Claude Code, Claude Enterprise, Amazon Bedrock, and Microsoft Foundry. Wells Fargo’s security team put it simply, saying their logs stay in a Wells-managed environment under Wells-managed keys. Cochrane adds a personal note on the same retention change. Because transcripts now persist thirty days after last touch, he can keep Claude Code threads open far longer and lean on clear without losing context. Google’s Fairwind Program Hands Patching to the Machines Google is running the same play from the defensive side. Normally, a human engineer must reproduce a security flaw, understand it, write a fix, then prove the fix broke nothing else. That can stretch to weeks, and attackers live in exactly that gap. Fairwind pairs two systems to close it. Gemini 3.8 Flash Cyber is a model tuned for security work. CodeMender hunts for flaws and writes the patches. Together, Google says they produce verified, deployment-ready patches in minutes, running inside the customer’s own environment. Access is deliberately restricted to three groups: national cyber authorities; critical infrastructure operators in healthcare, telecom, energy, and finance; and major technology platform providers. More than 650 partners are involved. Cochrane’s take centers on logging quality. Systems that emit specific, unique errors rather than generic ones let these tools find real issues almost immediately. Furthermore, he sees value in purpose-tuned models over general ones, since different training data and methodology surface gaps a single familiar model would miss. Meta Built an AI That Learns From Its Own Experts Every organization has two or three people who actually understand the hard systems. When they are busy, everyone waits. When they leave, the knowledge leaves too. Most AI assistants address this with retrieval, searching documents when you ask. Meta went the other way. A long-running offline process digests the source material ahead of time into more than 200 structured knowledge files, so the thinking happens before anyone asks. On top sit what Meta calls recipes, step-by-step procedures mirroring how a specialist actually works a problem. The reported numbers are concrete. Restructuring cut tokens consumed per turn by 80 percent. Assessments that took days now take minutes. The team built the whole system in six weeks across three sprints. Cochrane focuses on the feedback loop. Normally, an expert corrects an assistant in chat; the answer improves once, then the system forgets. Meta’s version compiles corrections into knowledge files and regression-tests them, so fixes stick without retraining the model. However, he raises two real caveats from his own attempts. Building those knowledge files is token-heavy, and codebases change. If the offline process does not rerun, the documentation drifts away from the code it describes. He also predicts this will become a service offered by AWS, GitHub, or GitLab rather than something each company builds alone. Sixteen Green AI Projects Across Asia-Pacific Google DeepMind named the first cohort of its Accelerator: AI for the Planet program. Sixteen organizations span New Zealand, Singapore, South Korea, Indonesia, Thailand, India, Australia and Japan, receiving three months of access to Google’s AI stack plus mentorship and a Singapore bootcamp. Several stand out. A New Zealand outfit called 800 Trust uses bioacoustics, monitoring an ecosystem by listening to it and running AI over continuous audio to track biodiversity. Wildlife.ai builds open-source AI camera traps. Australia’s X-Centric replaced the soil lab with a handheld X-ray reader that answers a farmer standing in the field. In India, Climitra Carbon verifies invasive species removal and converts the biomass into biochar. Access matters more than money, as Cochrane points out. A six-person conservation nonprofit cannot run frontier models, because the compute bill alone would consume its operating budget. The organizations closest to these problems have always been furthest from the tooling. An Oklahoma Bitcoin Mine Condemned After Leaking 3.8 Million Gallons Cochrane corrects the figure up front. Many outlets report three million gallons, but El Reno city officials put it at 3.8 million. A Bitcoin mining operation on West Jensen Road leaked water and dropped pressure badly enough to close El Reno Public Schools, the Canadian County Courthouse, and other city and county offices. It happened during a month with 24 days above 100 degrees, in a region under severe to extreme drought. The leak is not the damning part. The city issued a stop-work order on the site back in 2023 for electrical, construction, and fire safety violations, then never followed up. The facility ran roughly three years under an order nobody enforced. Interim city manager Ken Brown did not dodge it, saying simply, “We failed.” The site is now posted as condemned with a ten-day removal notice, and a hearing with operator Athlon BT is set for September 14th. Reaching the company has proven difficult, with a website stuck on a maintenance notice and an unanswered California phone number. Cochrane draws one distinction that the coverage keeps blurring. This is a Bitcoin mining rig, not a hyperscale AI data center. The residents who lost pressure absorbed the cost, and nobody billed the operator for the aquifer. BepiColombo Closes In on Mercury After Eight Years Reaching the closest planet to the Sun took nearly eight years, which sounds backward until you understand the physics. Falling toward the Sun means gaining enormous speed, and a spacecraft arriving too fast simply sails past. So the mission spent those years shedding velocity across nine gravity-assist flybys: one at Earth, two at Venus, and six at Mercury itself. On September 3rd, the transfer module separated and was discarded more than 200 million kilometers from Earth. Mission control marked the moment with “Roll call completed, GO for separation.” Importantly, the spacecraft has not arrived yet. Orbit insertion is November 21st, the two science orbiters separate around December 9th and 10th, and science operations begin in April 2027. That November date is revised, having slipped from an earlier plan. Two orbiters fly because they do different jobs. Europe’s Mercury Planetary Orbiter studies the planet and what lies beneath its surface. Japan’s Mio studies the magnetosphere. Mercury having a magnetic field at all is genuinely odd, since a planet that small should have cooled and lost it long ago. The mission honors Giuseppe “Bepi” Colombo, the Italian mathematician who worked out how to slingshot a spacecraft to Mercury in the first place. NASA Builds a Rocket Engine Talk You Can Hear NASA hosts a webinar on Friday, October 2nd at 2 pm Eastern, titled “The RS-25 Engine and the Future of Artemis Missions.” It runs about two hours, is open to anyone, and RSVPs close September 25th. The RS-25 is not new hardware. It is the Space Shuttle main engine, the same design that flew 135 shuttle missions across three decades, now bolted four at a time into the SLS core stage. Together they produce roughly 2.2 million pounds of thrust at 111 percent of their original shuttle rating. Throwing them away is the strange part. These are precision engines built to fly repeatedly, yet Artemis expends four on every launch. NASA got a proven engine and skipped a decade of development, and that is the trade. The accessibility work is the real story. The event includes an audio-described video of an engine test firing, a live Q&A with an Artemis engineer, and a panel on accessibility in space and science. A test firing normally sells entirely on spectacle. Conveying that, and the engineering underneath it, without the visuals is a genuine design problem NASA built the whole event around solving. Buried Underwear Wins a 2026 Ig Nobel The 2026 Ig Nobel Prizes were awarded September 3rd in Zurich. Marc Abrahams launched them in 1991 at the satirical magazine Annals of Improbable Research, and what began as a roast is now something researchers actively want. The soil science prize went to a team that buried 1,000 pairs of underwear across more than 25 countries and dug them up two months later. Measuring how much cotton rotted turns out to be a cheap, surprisingly good proxy for how biologically alive the soil is. The biomechanics prize recognized a precise, cross-species definition of kissing that works for animals and excludes passing food. By that definition, polar bears kiss, some birds kiss, and so do ants. Nature reports the behavior traces back roughly 21.5 million years to the ancestor of all large apes, meaning ancient humans very likely kissed Neanderthals. Cochrane’s favorite was the physics prize, awarded for a splash-free urinal design that reportedly cuts spray to 1.4 percent of normal. Cochrane closes by pointing listeners to the GNC Insider program, the newsletter, and podcastapps.com for a modern podcast app. Feedback on the show’s format is explicitly welcome at geeknews@gmail.com, where either Ray or Chris will read it. The post Anthropic’s $5 Million Push to Measure AI’s Effect on Wellbeing #1876 appeared first on Geek News Central.

Stephanie Palazzolo talks with TITV Host Akash Pasricha about OpenAI's new Astra model and its AGI claims. We also talk with Valida Pau about Coatue's proposed chip financing joint venture with startup MatX, Aaron Holmes about rising AI cyber threats and ElevenLabs' 2028 IPO plans, and we get into AWS's major Bedrock overhaul with Catherine Perloff.Articles discussed on this episode: https://www.theinformation.com/articles/anthropics-house-payments-tech-push-chip-away-stripehttps://www.theinformation.com/articles/coatue-matx-talks-new-multibillion-chip-financing-venturehttps://www.theinformation.com/articles/ai-threats-reshaping-companies-spend-cybersecurity-budgets https://www.theinformation.com/newsletters/ai-agenda/elevenlabs-hires-cfo-eyes-2028-ipohttps://www.theinformation.com/articles/six-aws-engineers-rebuilt-bedrock-challenge-microsoft Subscribe: YouTube: https://www.youtube.com/@theinformation The Information: https://www.theinformation.com/subscribe_hSign up for the AI Agenda newsletter: https://www.theinformation.com/features/ai-agendaTITV airs weekdays on YouTube, X and LinkedIn at 10AM PT / 1PM ET. Or check us out wherever you get your podcasts.Follow us:X: https://x.com/theinformationIG: https://www.instagram.com/theinformation/TikTok: https://www.tiktok.com/@titv.theinformationLinkedIn: https://www.linkedin.com/company/theinformation/

In this episode, Ray Cochrane breaks down Hot Chips 2026, the engineering conference where IBM, NVIDIA, Intel, AMD, Arm, and Fujitsu all showed how their next processors actually work. The headline disclosure is a mainframe core that runs Arm natively. Ray also covers Apple’s odd M6 Mac mini naming, London’s first autonomous Uber rides, Amazon’s purchase of the company behind DuckDB, GitHub’s HydraFusion, the best of IFA 2026, and new USDA research on farmed salmon. – Want to start a podcast? It’s easy to get started! Sign-up at Blubrry – Thinking of buying a Starlink? Use my link to support the show. Subscribe to the Newsletter. Email Ray if you want to get in touch! Like and Follow Geek News Central’s Facebook Page. Support my Show Sponsor: Best Godaddy Promo Codes Get 1Password Full Summary Cochrane opens the show with a personal update. He apologizes for the late rollout and the missed Monday episode, having spent the week fighting a cold. He’s also heading to Michigan to spend time with family and visit his father’s gravesite. He hopes to record a couple of shows from his dad’s old studio while he is there, including a special episode planned for Tuesday. He also points listeners to a fresh site redesign that trades the old techie look for something cleaner and friendlier. The featured segment starts from a wrap-up post on Arm’s newsroom. However, Cochrane broadens it to cover the whole conference rather than a single article. Hot Chips has run every August since 1989, and this year’s event was the 38th, held August 23rd through the 25th at Stanford’s Memorial Auditorium. What Hot Chips Actually Is Cochrane draws a line between Hot Chips and the big consumer trade shows. CES and Computex exist for product announcements and marketing. Meanwhile, Hot Chips is an IEEE engineering conference where chip architects present block diagrams and die photos for thirty minutes at a stretch. The audience matters as much as the content. Roughly five hundred people who design chips for a living fill the room, and they would spot a fudged number immediately. No written paper is required, just the talk and the slides. In-person tickets sold out this year, as did Stanford’s dorm housing. Cochrane says he plans to cover the conference annually going forward. IBM Built a Mainframe Core That Speaks Arm The disclosure that stopped Cochrane cold came from IBM. Its next processor for IBM Z and LinuxONE runs two completely different instruction sets natively, on every one of its eleven cores. Those are z/Architecture, IBM’s own mainframe language, and AArch64, which is 64-bit Arm. Crucially, this is not emulation. Nor is it Arm cores glued onto the die beside the mainframe cores. IBM built 2,792 Arm instructions directly into the hardware, which it says is more than double the mainframe instruction count. Each core carries two separate decoders while sharing the caches, branch predictor and register files downstream. It switches between the two in nanoseconds. IBM even added dedicated hardware to flip byte order, because Arm and the mainframe store numbers in opposite directions. The payoff is Arm SystemReady compliance, meaning off-the-shelf Arm Linux runs on a mainframe unmodified. Patrick Kennedy of ServeTheHome, who was in the room, wrote: “I am sitting here still in awe of what IBM is doing here; this is not Z plus Arm cores, this is Z and Arm in one core.” Cochrane flags one precision point that is easy to get backward. IBM did not license Arm’s core designs and drop them in. Instead, it took its own mainframe core and taught it AArch64 under an architecture license, which is considerably harder engineering. The specifications are striking. The chip uses a 2nm process, with eleven cores running above 5.7GHz sustained and no turbo mode at all. Each core gets 36MB of L2 cache, backed by a 3.5GB virtual L4 pool. Furthermore, the reliability target is eight nines, which works out to roughly three tenths of one second of unplanned downtime per year. IBM gave it no name and no ship date, though the press expects “Telum III” around 2028. Arm, Fujitsu and NVIDIA Show Their Hands Arm itself had plenty to discuss, starting with an unfortunate name. Its first chip in thirty-five years is called the AGI CPU, which is a product name rather than any claim about artificial general intelligence. For three and a half decades, Arm designed processor blueprints and licensed them out, collecting royalties without competing. That era is now over. The AGI CPU is Arm’s own silicon, co-designed with lead customer Meta, running up to 136 cores on TSMC’s 3nm process at 300 watts. Arm’s CEO says the company has more than $2 billion in customer demand across the next two fiscal years. Fujitsu brought the detail Cochrane called the coolest of the conference. Its MONAKA chip packs 144 Arm-based cores, but the trick is the cache. Rather than sitting alongside the cores and eating die area, the entire last-level cache lives on a separate 5nm die with the 2nm compute die stacked directly on top. It ships in 2027 in 350-watt and 500-watt versions. NVIDIA had more stage time than anyone, with six sessions. Its new Vera CPU carries 88 cores of NVIDIA’s own Olympus design, which marks a change: the previous Grace CPU used Arm’s off-the-shelf cores. Consequently, Arm’s win here is the instruction set, not the blueprint. The memory disclosure drew the most attention, with a fully loaded system reaching 1.5TB at 1.2TB/s while the whole memory subsystem draws just 30 to 40 watts. The Caveat on NVIDIA’s Benchmark Slides Cochrane pushes back on how NVIDIA presented its numbers. On the standard SPEC integer benchmark, Vera scored 925 against AMD’s 128-core EPYC score of 898, about three percent ahead. However, the slide NVIDIA showed normalizes that same result per physical core, which makes a three percent gap look enormous. NVIDIA defends the choice, arguing that per-core throughput matters when thousands of AI agents run at once. Cochrane grants that it is a fair argument to make. Even so, his verdict is blunt: it is a different number from the headline one, and presenting it that way is not the best look. Sponsor: GoDaddy Economy hosting $6.99/month, WordPress hosting $12.99/month, domains $11.99. Website builder trial available. Use codes at geeknewscentral.com/godaddy to support the show. Apple’s Newest Chip Landed in Its Cheapest Mac Last week’s episode covered the Mac Studio half of Apple’s August announcement. Tonight Cochrane takes the other half, the new Mac mini, and finds the numbering genuinely strange. The $899 base Mac mini gets the M6, which is Apple’s first 2nm chip and the newest process the company has shipped. It brings twelve CPU cores, twelve GPU cores, and 170GB/s of memory bandwidth. Apple also introduced a third CPU core class called super cores. So Apple’s most advanced chip sits in its cheapest desktop, while the M5 Pro, M5 Max and M5 Ultra above it all carry a lower number. It gets stranger. The M6 mini has Thunderbolt 4 while the pricier M5 Pro mini has Thunderbolt 5, and the memory ceiling runs backward too. Apple explains none of it across three announcement pages. Reading between the lines, Cochrane figures the M6 is the entry point of a new generation that shipped ahead of its larger siblings. London’s Robotaxis Started Carrying Passengers Arm’s monthly roundup covers everything outside the data center, and Wayve stood out. Transport for London granted the British self-driving company private hire vehicle licenses on August 5th, the same category a minicab needs. Then on September 3rd the service launched with Uber, marking the first autonomous rides ever offered to UK passengers. A small fleet of Ford Mustang Mach-Es covers anywhere in London except the airports, with a TfL-licensed safety driver still aboard. Over 140,000 Londoners signed up. The compute runs on NVIDIA’s Arm-based automotive platform, which is why Arm claims the win. Cochrane notes the pattern: once you set a standard nobody can move off, these wins keep arriving. Two more items round it out, both about squeezing AI onto phones. Google’s Pixel 11 shipped in August with the Tensor G6, and Google claims on-device AI runs up to 3.5x faster using 3.5x less energy. Those are Google’s own unbenchmarked figures. Separately, Graphcore’s research team worked with Arm to run an 11-billion-parameter vision model on phone-class processors by squeezing each parameter to 2.7 bits, taking the model from roughly 22GB down to 3.7GB. Intel Is Pitching AI Infrastructure From a Long Way Back Intel’s newsroom post previews the AI Infra Summit, running September 15th through 17th in Santa Clara. CEO Lip-Bu Tan takes a fireside chat on Tuesday morning, with three Intel sessions across the show. Cochrane unpacks two terms first. Physical AI means AI that acts in the real world through sensors and motors rather than living on a screen, and Intel takes it seriously enough to have renamed its PC division the Client Computing and Physical AI Group in May. Disaggregated inference splits the two phases of running a model: reading your prompt is compute-hungry, while writing the answer back is memory-hungry. The context is where this gets interesting. Intel’s revenue rose 25 percent last quarter, its fastest growth since 2011. Nevertheless, in AI accelerators the company barely registers next to NVIDIA. Gaudi has effectively been abandoned, to the point that Intel stopped maintaining its open-source driver, and AMD passed Intel in data center revenue last quarter. Tellingly, when Intel demoed disaggregated inference at Computex, NVIDIA GPUs handled one phase and SambaNova chips the other while Intel supplied the coordinating CPU. Crescent Island, Intel’s actual inference chip, does not sample until later this year, and Intel declined to publish its memory bandwidth. Amazon Bought the Company Behind DuckDB On August 26th, Amazon signed a deal to acquire DuckLabs, the Amsterdam company behind DuckDB. Cochrane spends time explaining what DuckDB is, since listeners outside the data world may never have encountered it. The problem it solves is familiar. Querying a large pile of data files traditionally meant either running a database server or spinning up a data warehouse with a cluster, a bill, and a loading pipeline. Both are heavy machinery for a question you wanted answered in ten seconds. DuckDB instead ships as a library rather than a server. You add it to your program like any other package, point it at your files, and write ordinary SQL directly against them. The data never moves. The usual comparison is SQLite, which is embedded in nearly every phone and browser on earth. Where SQLite excels at looking up one record, DuckDB rebuilds that embedded idea for chewing through millions of rows. It now sees roughly 62 million monthly downloads on Python’s package index alone, up from about 25 million last October. AWS says it is buying the company, not the project. DuckDB stays free and open source under the MIT license, held by a Dutch nonprofit foundation, and the founders join AWS while continuing to run technical direction from Amsterdam. Andy Warfield, a VP and distinguished engineer at AWS, described DuckDB as “the glibc of structured data: a lean, unglamorous, ubiquitous dependency that a great deal of software links against and almost nobody has to think about.” Cochrane sits with what that ownership means. He reaches for an analogy: imagine Daniel Stenberg selling curl. He doubts it would ever happen, but the concept alone is startling given how much infrastructure depends on it. His read is that AWS is betting DuckDB becomes as foundational as curl and SQLite already are. GitHub Has One AI Model Grade Another One’s Homework GitHub shipped Project HydraFusion into Copilot as a research preview. Instead of routing your request to a single model, it picks one of three approaches per request. Sometimes one model simply answers. Alternatively, a cheaper model drafts, and a quality gate decides whether to escalate. The interesting one is Critique. One model writes the code, a separate model from a different family reviews it read-only, and the original gets one pass to revise. Despite the name, nothing is fused here. There is no voting and no merging, just one model at a time with a gate deciding whether to spend more. GitHub explained the reasoning in an earlier post: “a model reviewing its own work is still bounded by its own training biases: the same training data and techniques, the same blind spots.” Research supports it. A team at NeurIPS in 2024 showed that models recognize their own writing and score it higher than human graders do. GitHub’s earlier number had a Claude Sonnet and GPT critic pairing closing about three-quarters of the gap between Sonnet and the larger Opus model. This mirrors a workflow Cochrane uses constantly and has described on a previous episode. He runs a cross-check review with a second model from a different company, and it routinely surfaces issues the first model missed. He explains that different training data, different engineers, and different reinforcement approaches build different internal biases about what counts as correct. Looking ahead, he expects more of these “Frankenstein patterns” where models from different training families work together. The Best of IFA 2026, and What You Can Actually Buy IFA opened to the public in Berlin for its 102nd year, with about 1,900 brands. Cochrane splits The Verge’s roundup in two, since much of what generates headlines at these shows never ships. Starting with real products, iRobot’s flagship Roomba Max 875 Combo runs $1,199 and ships in about two weeks. Its SealForce feature drops a hidden skirt from the chassis when it detects carpet, sealing against the fibers so suction concentrates instead of leaking out the sides. That reaches 35,000 pascals, iRobot’s strongest yet. A step-down model at $899 carries the same trick, though Cochrane balks at both prices. Anker’s Soundcore Sleep 4 Pro earbuds arrive in November at $349.99. The charging case carries its own round touchscreen, so you pick soundscapes, set alarms, and read sleep stats without your phone. Optical sensors read heart rate and variability from the ear canal, which beats the wrist for accuracy, and the case masks a snoring partner. Cochrane remains unconvinced about sleeping with earbuds in. Philips also has smart rope lights, the Hue Liane 360, on sale now. They glow evenly around the tube rather than showing individual LEDs. They also run $400 for three meters, which works out to about $130 per meter of rope light. As for concepts nobody can buy, iRobot showed a robot vacuum that carries a smaller robot vacuum on its back in a garage and lowers it to deploy. Lenovo brought a 14-inch laptop whose screen rolls out to 17 inches at the press of a button, which reviewers call the first rollable that feels close to shippable. Tecno showed a phone with essentially no border around the screen, and Acer had a Windows gaming handheld that swivels its screen up over a keyboard. Two themes ran through the show. Humanoid robots were the loudest thing on the floor, and IFA’s own CEO framed the event as being about robots that work rather than robots that demo. Meanwhile, AI stopped being its own product category and became an ingredient, showing up in refrigerators, treadmills, dishwashers, and motorized TV mounts. Farmed Salmon Isn’t the Omega-3 Machine It Used to Be USDA scientists measured farmed salmon and found considerably less of the good fat than the government’s own database claims. EPA and DHA are two fatty acids you get almost entirely from fish. Your body can build them from the plant version, but only in tiny amounts, so the NIH’s position is that eating them is the only practical way to raise your levels. Those fatty acids are structural pieces of every cell, with DHA concentrating in the brain and retina. That is why the federal dietary guidelines, issued jointly by USDA and Health and Human Services, recommend at least eight ounces of fish a week and steer you toward salmon. That amount is calibrated to deliver about 250 milligrams a day. Published in Frontiers in Nutrition last month, the study found EPA and DHA in farmed Atlantic salmon came in 54.7 percent lower than USDA’s own reference values, last updated in 2018. A three-ounce serving fell from roughly 1,670 milligrams to about 756. Consequently, two servings a week now fall about 14 percent short of the target. Plant-derived fats meanwhile rose two to three times over. The likely cause is feed. Salmon are carnivores, and farms once fed them oily little fish. There was never going to be enough of those as the industry scaled, so crops filled the gap: soy, canola, sunflower and linseed. Importantly, the study does not claim to have proven this and calls the feed shift a plausible explanation. Independent corroboration lends it credibility. Researchers at Stirling measured a similar halving in Scottish salmon between 2006 and 2015, and Norway’s marine institute saw it across thousands of samples. There is a land dimension too. Roughly half the world’s soy grows in South America, where rainforest gets cleared for feed. Matthew Hayek, who studies the environmental cost of protein at NYU, told Inside Climate News that “soy is a major, important protein and oil ingredient in fish farming.” Adding up two decades of soy across all fish farming, he puts the extra forest clearing at around the area of Nicaragua or Bangladesh. That figure covers all fish farming rather than salmon alone, and Hayek notes it is hard to attribute soy use to any single species. Cochrane closes with two caveats. First, the study measured only eight fish, bought around Maryland, DC and Virginia over six weeks in 2023, and nearly all sourced from Chile. That is not a national survey, and the authors say plainly the sample was not large enough to change government advice. Rather, it flags that a federal database value needs rechecking, which is what the paper set out to do. Second, on whether you should care, farmed salmon still beats beef, chicken and eggs by a mile, since those carry essentially zero EPA and DHA. What it loses is its crown among fatty fish, dropping to mid-pack behind herring, sardines and mackerel and roughly level with trout. The broader health case is also softer than the 2000s suggested. A review of 86 trials covering 162,000 people found supplements barely moved heart attacks or deaths, so eating fish and swallowing fish oil are not the same claim. No producer has responded to the findings, and USDA, whose own scientists ran the study, declined an interview and did not answer emailed questions. Cochrane wraps up with housekeeping and a note that he will be back on Labor Day. The post The Mainframe Learned to Speak Arm #1875 appeared first on Geek News Central.

Welcome to another edition of Retail Roundup. This is your weekly brief helping retail leaders decode the biggest shifts in retail, AI, and commerce. In this week's episode, Jeremy Goldman sits down with Sky Canaves (Principal Analyst, EMARKETER), James Tenser (Storyteller-in-Chief, CPGMatters), and Lavina Suthenthiran (Senior Retail Analyst, RETHINK Retail) to discuss a shaky IPO, a widening apparel gap, and what's really building shopper trust in 2026. IN THIS EPISODE, THE PANEL BREAKS DOWN: - Shein's anticlimactic Hong Kong IPO. After years of regulatory setbacks in New York and London, Shein finally went public at roughly a quarter of its 2022 valuation. The panel unpacks why investor enthusiasm cooled and whether Shein's real long-term opportunity is less about fast fashion and more about becoming an AWS-style supply chain service for other brands. - Amazon's growing grip on apparel. Amazon's share of US clothing spend has doubled since 2019, while Walmart's has stayed flat. The group examines broader brand selection, easier returns, and an AI shopping assistant that's quietly reshaping how people discover what to buy. - Target's beauty reset draws scrutiny. Following its split from Ulta, Target's new in-house beauty assortment features just 2% Black-owned brands, a percentage that's raising questions given the company's prior commitments and recent DEI reversals. - Physical retail might be the best ad you're not counting. The group explores how a store's mere presence, even one a shopper never enters, can build the trust that drives online conversion. Listen now for the full conversation.

A structural shift in regulatory accountability now places incident notification and liability directly on the operators or deployers of AI-powered and software tools, rather than on technology vendors or model developers. This mechanism is made explicit by the requirements of the EU's Cyber Resilience Act (CRA), Digital Services Act (DSA), and the upcoming Machinery Regulation. Incidents such as the Cursor AI coding agent breach at a Belgian chemical company underline that compliance timelines and regulatory scrutiny target the entity deploying the technology.CrowdStrike and Okta both reported that increased enterprise security spending is being driven by heightened AI-generated attacks, according to their quarterly results. Gartner forecasts AI security spending will reach $4.8 billion by 2027, up 68.7% from this year, with usage control as the most dynamic segment. A public letter signed by over 100 vendors—including OpenAI, Anthropic, AWS, and Microsoft—warns of urgent defensive needs but does not shift responsibility to software suppliers.Recent breaches and vulnerabilities illustrate how accountability remains with the service provider or end-user implementer. The Cursor breach assigned notification duties to AnySphere (the product vendor) and the breached organization, not to upstream model providers. Likewise, after N-able's Passportal bug, MSPs were accountable for client-facing remediation. In each case, the “accountability line” lands on the party deploying the tool.For MSPs and IT service providers, these trends require updating agreements, operations, and client communications. Service structures must prioritize regulatory response timelines, documentation, and clear reporting obligations. Providers serving EU clients, or those linked to global supply chains, will encounter business risk if they do not proactively address these regulatory demands before mandated deadlines.00:00 Prevention Got A New Price 03:25 The Half That Doesn't Move05:50 Where The Call Lands09:27 Why Do We Care? Supported by: Proofpoint GoTo(LogMeIn)

Join us as Cobus Bernard takes us on a live tour of his sprawling homelab - and explains why Claude wrote most of the Terraform and Ansible running it. Cobus walks through a Proxmox setup running Traefik, Vault, Nomad, Keycloak, and a three-node Kubernetes cluster that doesn't quite work yet, all built by handing infrastructure-as-code tasks to Claude and slowly deciding how much of it to trust with real commands. You will learn how Cobus structures Terraform state and variables so an AI agent can safely extend it, why he still won't let Claude run terraform apply unsupervised, how MCP servers control what an agent is allowed to touch, and why confabulation might be a better word than hallucination for what these models actually do. Timestamps 0:00 Welcome & Introduction 8:50 What's Running in the Home Lab - Proxmox, Traefik, and Vault 13:48 A Kubernetes Cluster That Doesn't Work Yet 17:09 MCP Servers and What Claude Is Allowed to Run 21:46 Is It That Claude Wrote the Terraform? 23:06 Trusting Claude with Terraform Apply 27:43 The Home Assistant Confession - Copy-Paste vs. Actually Learning 36:57 Naming Things - Solving the Classic Kubernetes Problem 43:52 Confabulation - A Better Word for AI Hallucination 48:49 Building a Tax Calculator App With Claude How to find Cobus: https://www.linkedin.com/in/cobusbernard/ Links from the show:

Mark Zuckerberg argues that broadly distributed personal AI, or a “superintelligence” in his parlance, can increase prosperity and counter the risks of AI being controlled by a handful of government and corporate entities. Drew Conry-Murray joins Eyvonne and William to engage in a lively roundtable where they examine whether distributing access meaningfully distributes power when... Read more »

Mark Zuckerberg argues that broadly distributed personal AI, or a “superintelligence” in his parlance, can increase prosperity and counter the risks of AI being controlled by a handful of government and corporate entities. Drew Conry-Murray joins Eyvonne and William to engage in a lively roundtable where they examine whether distributing access meaningfully distributes power when... Read more »

How can governments and public-service organizations adopt AI quickly while protecting the people affected by their decisions? In this episode of Tech Talks Daily, I speak with Holly Ellis, AWS Director for UK, International Organizations and Germany Public Sector Technology. Holly has worked on both sides of public-sector technology, with previous roles in local and central government before joining Amazon. She now leads teams supporting customers across education, healthcare, nonprofit organizations, local government and central government. We discuss why public-sector technology adoption depends on a wider system of governance, procurement, regulation, culture and skills. Holly cites AWS research with Strand Partners showing that half of UK public-sector organizations identify shortages in AI and digital skills as their main adoption challenge, up from 46 percent in the prior year. Over the same period, reported AI adoption rose from 52 percent to 64 percent. Her point is simple: greater adoption creates demand for a larger number of people with deeper knowledge. Holly also explains what responsible speed looks like when AI supports services involving education, healthcare or national institutions. Her approach is to think big, start small and scale fast, containing the effect of failure while teams build confidence. University clearing offers one example. Several universities used Amazon Connect during A-level results, with one institution handling up to three times the call volume of its previous system and confirming a four-figure number of student places in one day. The conversation then turns to safeguards. Holly argues that leaders must define organization-wide protections while engineers remain responsible for the systems they build. Depending on the consequence, those protections may include human review, observability measures and tightly scoped permissions for AI agents. At the Ministry of Justice, AWS Transform processed 24,000 lines of code during an initial nine-hour pass and completed a second pass in two hours. Human review took about 20 hours, compared with an estimated nine months for manual modernization. We also consider legacy technology, digital sovereignty and the difficulty of measuring AI outcomes. Holly describes sovereignty in practical terms as control, transparency and optionality. She advises leaders to define the outcomes they intend to measure before selecting initiatives, then build upon work that demonstrates the strongest returns. According to the AWS research discussed, organizations redesigning workflows and decision-making with AI reported average efficiency gains of 68 percent, compared with 40 percent among basic users. The wider lesson is that responsible public-sector AI depends on technical choices, people, governance and evidence working together. Can public services become faster and more responsive while retaining the safeguards and public confidence they require? Listen to the conversation and share your thoughts with me.  

Take a Network Break! We start with listener followup about how Device Bound Session Credentials could thwart session cookie theft, and then highlight a string of critical vulnerabilities in IBM’s AIX. On the news front, Nvidia has reportedly bought Hugging Face for $12.9 billion, Nvidia and AWS team up on GPUs and physical AI, and... Read more »