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Nearly 20 years ago (!), in 2007, I published my first and only book: Microsoft 2.0. It focused on changes I expected at the company in the “Post-Gates” era. What would remain the same and what likely would be different once co-founder and CEO Bill Gates had left the building?

CEO Satya Nadella has not exited the company (yet). But there’s no question that Microsoft and its mission have morphed considerably in the past year or two. I’m not quite ready to christen this the Microsoft 3.0 era, even though Nadella handed the reins of Microsoft’s dominant commercial business to Judson Althoff nearly a year ago.

That decision resulted in Nadella moving into more of a “founder mode” role, allowing him to focus less on the day-to-day work of running the business. (Microsoft historians may recall that Gates made a somewhat similar move back in 2000 when he became Microsoft’s chief software architect.)

While it might not yet be time for Microsoft 3.0, we arguably could be in the “Microsoft 2.5” era. Windows and Office are still around and still play a big role. Microsoft still builds and sells developer tools and databases. But there’s no question that the cloud and all things AI are at the top of the pecking order now.

I’m embarking on a series here at GeekWire that will focus on what matters to Microsoft and, by extension, to its customers, partners, investors, and employees these days. Who are some of the people shaping and leading the company? What are their opportunities and challenges right now?

Over the next few weeks, I will be profiling various Microsoft execs working on plans for Microsoft’s ongoing evolution. Some are company veterans; some are newcomers. I’ll be talking with top execs from Microsoft’s Security, Copilot, Windows + Devices, Xbox, GitHub, and more.

I’m interested in their strategies for Microsoft’s key products and technologies and how they plan to try to turn Microsoft’s ambitious vision into reality. What are their teams building? What do they see as their biggest challenges and opportunities? And where do they see the technologies in their respective areas heading?

I feel like many of us who’ve been keeping track of the biggest tech companies (myself included) have fallen into the trap of blaming or attributing everything a company does to AI. Layoffs? AI is the culprit. Price increases? It’s all thanks to AI. Changing sales strategies? Chalk it up to AI …

But upon further reflection, I believe Microsoft’s strategy is more nuanced than “AI or bust.” There’s no question that Microsoft’s AI ambitions are shaping its goals and tactics. But Microsoft, as a heavily enterprise-focused entity, can’t simply stop supporting products that aren’t built from the ground up with AI (as much as it might like to do so). Nor can it just leave behind customers who aren’t 100% onboard with its AI moves.

Couple those enterprise hurdles with some not-so-popular consumer decisions, like axing 3,200 people in the gaming unit, and Microsoft’s approach to turning the ship looks a lot trickier.

Our Microsoft 2.5 series kicks off Thursday. Stay tuned.

The combination of hardware required to make use of this project is specific enough that we imagine only a relatively limited number of readers will actually be able to try it out. But if you do happen to own a YubiKey and either a laser engraver capable of marking it or a fancy UV printer, [madeinoz67] has put together an awesome tool for adding some visual flair to your two-factor authentication device.

Running it is as simple as opening a web page, because that’s exactly how it’s implemented. You can either host it yourself or just launch it right from the GitHub repository. After opening the HTML file, you’re presented with a fairly intuitive user interface that lets you draw on top of a 2D outline of the YubiKey itself so you can get a better idea of what the final product will look like.

You can pick from an array of vector icons, upload your own images, and add custom text. There’s a pull-down at the top that lets you pick which specific YubiKey you want to work with, and there are different views depending on whether you plan on blasting your handiwork onto the device with a laser, doing a full-color UV print, or cutting it out of vinyl with something like a Cricut.

Even if you don’t have a YubiKey that’s begging for some custom artwork, we think there’s a lot to learn from this project. Obviously there are some very valid reasons to be concerned about how much of our modern software can only be accessed through a browser. If you’re going to use web technologies to create a piece of software, the least you could do is make it offline and self-contained like [madeinoz67] has.

Now if you’ll excuse us, we’ve got to go warm up the UV printer.

Bitcoin Magazine

Bitcoin Maxi Jack Dorsey Unveils New Open Source Group Chat App

Tech entrepreneur Jack Dorsey has announced a new group chat platform aimed at reducing teams’ reliance on platforms like Slack, in the Bitcoin maxi’s latest push for decentralization. 

The Block co-founder wrote Tuesday on X that the new app, named Buzz, was “for teams of people and agents of all sizes” and “model-agnostic, decentralized, self-sovereign, and open source.”

Described as “A new native workspace for human and agent teams” on its website, Buzz users can “chat with teammates and specialized agents in one shared space, then move straight into planning, project management, coding, and PRs.”

A statement from parent company Block said that the new app was built on decentralized social networking Nostr protocol.

“The interface will feel familiar to anyone who’s used a modern team communication tool,” Block added. 

“Every company is going to need a place where humans and agents work together,” Bradley Axen, head of AI capabilities at Block, said. 

“The question is whether that place is proprietary or open. We built Buzz because we believe it should be open.”

Decentralize everything 

Dorsey, whose firm Block owns companies Square and Cash App, has long been pushing for decentralized solutions: primarily with Bitcoin. 

The billionaire founder of Twitter left the social media company to focus his efforts on payments and Bitcoin adoption in 2021, saying he wants the cryptocurrency to be the global currency and “everyday money.” 

He has also described Satoshi Nakamoto’s Bitcoin white paper as “poetry.”

Cash App allows users to send and receive and buy and sell Bitcoin and point-of-sale terminals Square accept the orange coin via the Lightning Network. 

Block also last year debuted a Bitcoin mining rig with swappable parts, with the idea that miners could cut costs on repairing and replacing the devices. 

This post Bitcoin Maxi Jack Dorsey Unveils New Open Source Group Chat App first appeared on Bitcoin Magazine and is written by Mathew Di Salvo.

Intelligence does not have to be artificial.

The goal of this field was always to reproduce what a brain does. Somewhere along the way “artificial” stopped meaning inspired by the real thing and started meaning nothing like it — enormous, power-hungry, and opaque.

You’re tired of AI launches and IPOs? So am I. Every week there’s a bigger model, a longer context window, another benchmark nobody outside the lab can reproduce — and underneath it, the same machine doing the same thing a little faster and a lot more expensively. I mean, just looking at my emails these days is making me nauseous. I do not even check my social media anymore, and even less the stock market.

But, instead of complaining and be satisfied with the status quo, I decided to look at the problem from a different angle.

The main problems everybody knows without knowing it…

AI is expensive (yet, it does not have to be)

The cost problem isn’t separate from the design. It falls out of four choices that the field made early and never really revisited.

1- It reasons in the dark. Which makes hallucination or fake generation very hard to catch, yet to fix. Hidden states are well, hidden.

2- Scale is not intelligence. The reflex has been to make the model bigger and hope understanding shows up (it never will, the bigger the model, the more “links” it can do between concept and give the illusion of understanding). Scale = $$$$$$$$$$$$$$$.

3- Biology as the last of their concern. The brain runs on about twenty watts, and that number is a challenge, not a footnote. While we cannot make an AI that works on 20watts we can definately reduce the amount of energy consumption.

4- The root of it is profit. Not science. Even OpenAI leader is confirming it by saying that AI will eventually be sold like electricity and water — by companies like OpenAI. Article link: https://www.businessinsider.com/sam-altman-ai-utility-electricity-water-openai-2026-3

Now let’s talk about what it was supposed to be from the start

The goal of this field was always to reproduce what a brain does. Somewhere along the way “artificial” stopped meaning inspired by the real thing and started meaning nothing like it — enormous, power-hungry, and opaque.

I think we need to take the biology seriously instead of metaphorically: real neural mechanisms, a memory that consolidates the way a hippocampus does, a neurochemistry that actually modulates behaviour, learning that happens as the system runs rather than only in an offline training run. Those are design constraints, not decoration. And will lead to the “second generation” of AI.

The myth of AGI

a very convenient one if what you need is a reason to keep raising money.

While I have been plain, here’s where I don’t stand: AGI. The industry’s favourite three letters do a lot of quiet work — a general, human-beating machine, forever a few years and a few hundred billion away. It’s a wonderful story — or a frightening one, depending on where you stand — and a very convenient one if what you need is a reason to keep raising money. It’s a poor description of what these systems actually are, and a worse goal to organise a field around.

It’s a poor description of what these systems actually are, and a worse goal to organise a field around.

And the way today’s models are built won’t get there — not for lack of ambition, but for reasons you can put numbers on. Large language models improve along a scaling curve, and that curve has a shape: the returns diminish. Each new increment of capability takes not a little more compute but multiples more; the graph everyone cites bends the wrong way, flattening as the bill climbs. Every training run costs more than the last and buys less than the last one did. That isn’t a detail better engineering erases. It’s the shape of the method itself.

Every training run costs more than the last and buys less than the last one did. That isn’t a detail better engineering erases. It’s the shape of the method itself.

Now set that against a hard limit: power is finite. You can’t answer a curve of exponentially rising cost with an infinite supply of energy, because there isn’t one. A method whose only real lever is “make it bigger” runs into a wall that isn’t philosophical — it’s thermodynamic. Somewhere on that curve the next run stops being affordable, then stops being physically possible, long before it stops being merely better at text.

You don’t get a different kind of thing by making the same thing bigger

And that’s the deeper point: what scales here is fluency, not understanding. A model trained to predict the next word learns the statistics of language extraordinarily well. It doesn’t thereby acquire a grounded model of the world, a cause it can reason about, or a memory it can update — and no amount of the same training conjures those out of more of the same text. You don’t get a different kind of thing by making the same thing bigger. You get a costlier version of the same thing. A transformer is, underneath, a very good text generator; scale it and you get a better text generator — not a mind that understands, and not consciousness quietly emerging from the weights. Fluency is not comprehension, and no quantity of the first ever becomes the second. Something like general intelligence, if it’s reachable at all, will come from a different design — grounded, able to reason step by step, able to learn as it runs.

The point of this work was never to conjure a god

The point of this work was never to conjure a god. It was to build something genuinely useful — that reasons, remembers, and helps — and to run it on hardware people can actually afford. Intelligence doesn’t have to be general to be worth having, and it certainly doesn’t have to be a superbeing to earn its keep. Chasing AGI is how you end up with the bill on the other pages. Building something useful, efficient, and yours is how you don’t.

What a discovery is for, and how it gets used, stays a human call — the machine widens what we can see; the judgment is still ours.

None of this means the tools are useless — the opposite. An AI can read across billions of documents and surface a link between two of them in seconds, connections no person would ever stumble on alone. That is a genuinely powerful research instrument, and we build with it every day. But it won’t know what to do with what it finds unless someone told it beforehand what to look for and why. Finding is not deciding. What a discovery is for, and how it gets used, stays a human call — the machine widens what we can see; the judgment is still ours.

The danger isn’t the tool

If one ever goes autonomous and causes genuine harm, it will be because a person somewhere pointed it that way —

Some people will tell you AI is the real long-term danger. We’d put it the other way around: the danger is us. A model does what it is built and instructed to do. If one ever goes autonomous and causes genuine harm, it will be because a person somewhere pointed it that way — wrote the objective, wired it to something it should never have touched, or pulled out the guardrails that other people had put there in the first place. Even the runaway story needs a human at the start of it: someone to build it, aim it, and take it off the leash. Even if it escapes, a human had to set it loose or dare it to.

That isn’t a reason to be careless — it’s the opposite. It means the responsibility is ours and stays ours, which is exactly why we should keep the reasoning legible and the controls somewhere a person can see them. A tool you can read is a tool you can hold to account. That matters far more than pretending the machine has a will of its own.

Now time for a little shameless self-promotion ;) I built Grillcheese Research Laboratory exactly to study, learn and solve those problems and share how to do it with as much people as possible. I invite you to check the link to our website if you are curious. https://grillcheeseai.com

Let me know in the comment what you think and if you have more ideas / different views / links.

Thanks for reading and have a wonderful day!

Yours, Nick

Beyond A.I. was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story.

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Putting the Traeger to work on Thanksgiving has become one of my favorite ways to do the holiday. The kitchen stays clean, you’re not hovering over the stove all day, and everything just tastes better with a little smoke. This round-up covers a full Thanksgiving spread — smoked turkey, glazed ham, sides like cornbread and […]

The post 31+ Traeger Thanksgiving Recipes appeared first on Simply Meat Smoking.

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Hackers stole names, addresses, Social Security numbers, credit/debit card numbers, and other information from a third-party management platform.

The post Ernst & Young Data Breach Affects Personal, Financial Information appeared first on SecurityWeek.

This week on the GeekWire Podcast: Silicon Valley legend Vinod Khosla’s family is leading a group that’s buying the Seattle Seahawks for a record $9.6 billion.

We dug into hours of his talks and interviews to answer the big questions: Who is this guy, why does he want an NFL team, and what does his track record tell us about the kind of owner he’ll be? Plus, the blind spot that could get him into trouble.

Featuring highlights from his 2015 talk at the Stanford Graduate School of Business.

Also: A mystery trove of aerospace artifacts is rescued from a Seattle-area electronics recycler, and we want to hear about your coolest tech history find. Send your comments, voice memos and photos to todd@geekwire.com.

Subscribe to GeekWire in Apple Podcasts, Spotify, or wherever you listen.

The choreography in Ankara last week was impressive, even by Recep Tayyip Erdogan's standards. Cannons fired, mounted honor guards paraded, and jets flew overhead trailing red, white, and blue smoke as Donald Trump arrived for the NATO summit. By the time the two leaders sat down together, the American President was already telling reporters that Turkey has been "much more loyal" than other allies, and that reinstating Ankara into the F-35 program is "certainly something we will consider." He went further, promising to lift the sanctions imposed under CAATSA after Turkey's 2019 purchase of the Russian S-400 air defense system.

Washington should slow down and reconsider any such move. The temptation to reward Erdogan for a good show of pageantry and for playing a useful back channel to Tehran is understandable. But the case for readmitting Turkey to America's most sensitive fighter jet program does not hold up, and the reasons go well beyond the S-400 that got Ankara expelled in the first place.

Let’s start with Turkey’s original sin. Turkey was removed from the F-35 program precisely because the S-400 system stationed on Turkish soil poses a collection risk to the F-35's stealth signature and sensor data. Nothing about that system has left the country. Trump's own suggestion that he has "no concerns at all" about Turkey operating Russian and American systems side by side ignores the technical judgment his own administration reached in 2019: an S-400 battery within range of an F-35 is an intelligence-gathering platform aimed at the jet's most guarded secrets.

Turkey now appears it wants to atone for its sins: In the days that followed the NATO summit, well-placed sources in Ankara announced Turkey’s intention to sell or transfer its S-400s to another country, possibly Qatar or the United Arab Emirates. Doing so may satisfy the letter of the law, section 1245 of the 2020 National Defense Authorization Act, which bars F-35 transfers to Turkey unless Washington certifies Ankara no longer "possesses" the S-400.

Then come regional concerns. Israel has lobbied hard against the F-35 sale, with Prime Minister Benjamin Netanyahu warning that Turkish F-35s would erode the air superiority that guarantees Israeli and American posture across the Middle East. Athens and Nicosia have made similar appeals, citing Turkey's continued military pressure in the Aegean and its decades-long occupation of northern Cyprus. These are warnings from allies and partners who would sit on the receiving end of Turkish airpower upgraded with fifth-generation stealth.

But there is a fourth danger that has drawn far less attention in Washington, and it may matter more than any of the others: Turkey's telecommunications backbone is no longer fully Turkish. The country's leading systems integrator, Netaş, is roughly 48 percent owned by ZTE, and Huawei is deeply embedded in the networks operated by Turkcell, Türk Telekom, and Vodafone Turkey. Under China's 2017 National Intelligence Law, that ownership is not a passive investment. Beijing can compel any Chinese firm, anywhere it operates, to hand over data on demand, and corporate assurances of independence carry no legal weight against that obligation.

Washington has already treated this exact problem as disqualifying. In 2021, a $23 billion F-35 and drone package for the United Arab Emirates collapsed, in part because Huawei was building Abu Dhabi's 5G network and American intelligence had identified a suspected Chinese military-linked facility at Khalifa Port.

Turkey’s embrace of Chinese telecoms also cuts against the Alliance’s moves towards securing the critical infrastructure underpinning its military mobility — the bridges, rail links, and digital networks that allow allies to uphold deterrence. Across the continent, these networks have become a critical target over the course of the war in Ukraine, as adversarial actors linked to Russia use grey zone tactics to undermine collective resilience and damage alliance cohesion.

Washington increasingly views countering this threat as a top priority. In May, the Trump administration urged NATO members to spend a portion of the 1.5 percent of GDP allocated to defense-related spending on removing Huawei components from their domestic networks, highlighting the vulnerabilities posed by Chinese equipment and hacking campaigns such as Salt Typhoon. While that call is already being heeded by several NATO allies — Sweden and the UK have been particularly proactive in securing their systems — Ankara remains a laggard, undermining its contribution to alliance interoperability.

The risks are not simply tied to the F-35 itself, but to its entire operating environment. If sold, the fighter will be operating within an ecosystem saturated by Chinese-produced telecom equipment, reliant on a deployment infrastructure whose roots directly tie back to Beijing, operated by a capital pulling in the opposite direction of a key Alliance priority. While the U.S. has heavily invested in protecting the F-35, no system is ever fully secure, and any sale would force the jet to operate in a vulnerable environment for decades to come.

Turkey’s pending S-400 sale may remove dangerous hardware, but it does not eliminate the systemic risk associated with the deal.

The Cipher Brief is committed to publishing a range of perspectives on national security issues submitted by deeply experienced national security professionals. Opinions expressed are those of the author and do not represent the views or opinions of The Cipher Brief.

Have a perspective to share based on your experience in the national security field? Send it to Editor@thecipherbrief.com for publication consideration.

Read more expert-driven national security insights, perspective and analysis in The Cipher Brief

Apple Car Key support is reportedly coming to future GWM Tank SUVs, allowing compatible iPhone and Apple Watch users to unlock, lock, and start their vehicles digitally.

The post Apple Car Key Support On The Way To Future GWM Tank SUVs first appeared on Redmond Pie.