Doc Searls Weblog

Just trying to make stuff happen

  • Theday

    Will I ever run out of new names for days of the week? We'll see.

    Markets are Money

    It doesn't say that in The Gluetrain Manifesto, but the long-gone (but archived) parody of The Cluetrain Manifesto is still funny.

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  • Webnesday

    Visualization (by Gemini) of the baffling trade of Jaylen Brown, one of the league’s top-tier players, to the 76ers, for the aged and often-injured Paul George.

    The worst trade since Luka for whatever that was

    Something very very bad must have happened to kill the relationship between Jaylen Brown and the Boston Celtics, a team JB loved and led to performance levels far above expectations this past season. At the end of that failed relationship came one of the worst trades Boston GM Brad Stevens has ever made: Jaylen Brown to the Sixers for Paul George and some picks. I feel bad for Celtics fans and for the team. I also feel bad that the Knicks just lost Mitchell Robinson to the Celtics, but that was a free-agent move, not a trade. The Knicks will be fine. I think they’ll win the East again, and maybe repeat as champions. But the Sixers scored a heist, and the Celtics are far worse off.

    From bad to wurst

    NOYB: US Supreme Court just blew up EU-US Data Transfer., further worsening, um…  everything. But we’re getting used to that. Here’s the decision.

    This is good. Very good.

    The new Declaration by MyData says this:

    Everyone can contribute to achieving the MyData mission – individuals, communities, organisations, policymakers, service providers, technology innovators, entrepreneurs, researchers, funders and many more.

    I added the link. Here’s a collection of my own writings about MyData (IEEE 7012).

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  • Moosday

    We'll see what happens

    Call for Tenders: Development, consultancy and support for a data altruism consent management system went out from the European Commission on 27 May of this year. It begins, "This call will fund a robust, legally compliant and user-friendly digital solution that enables individuals to give, withdraw and manage consent for data altruism purposes." It's due today.

  • Unday

    And in your browser, it's hard to tell who's winning

    Remember "fair use"? It's a concept kind of like "public airwaves." There's an ideal in there somewhere, but the context is a world where social contracts really aren't, and it's all kind of worked out, but not really. Alex Raksin tackles "fair use" in How to Copyright the Weather. His explanation is as lucid as one can be about a topic (or set of them) that could hardly resist it more:

    Our law treats text as property—a thing you can borrow, return, or fence off. The machine treats text as atmosphere—a pool of probabilities it breathes in. These soft laws are trying to use the vocabulary of real estate to regulate the weather.
    Both the hard law and the soft, in short, are failing to resolve the tension between content owners and content users.
    So two opposite things are now happening at once. From below, resistance: software developers building tools like Cloudflare’s Pay-Per-Crawl marketplace, which flips the default so AI crawlers are blocked unless a publisher lets them in—free, or for a per-crawl fee the publisher sets. From above, capture: the tech titans simply routing around the public fight by signing private contracts, quietly converting what used to be an open information commons into an elite network of paid toll roads. It isn’t yet clear which direction wins.

    Linkages

    On Your Terms. Needs to connect to MyTerms.

    What If Every Massachusetts Resident Had Their Own AI Agent?

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  • Someday

    Loose links

    Hermes Agent, and Hermes Agent. Both new to me, but look important, because it's open source personal AI. Not clear yet on the difference.

    Privacy Manifesto. Wrote it years ago. Does it need an update?

    Reckoning with the Political Economy of AI: Avoiding Decoys in Pursuit of Accountability, by Janet Vertesi, danah boyd, Alex S Taylor, and Benjamin Shestakofsky. The abstract begins,

    The Project of AI is a world-building endeavor, wherein those who fund and develop AI systems both operate through and seek to sustain networks of power and wealth. As they expand their access to resources and configure our sociotechnical conditions, they benefit from the ways in which a suite of decoys animate scholars, critics, policymakers, journalists, and the public into co-constructing industry-empowering AI futures. Regardless of who constructs or nurtures them, these decoys often create the illusion of accountability while both masking the emerging political economies that the Project of AI has set into motion, and also contributing to the network-making power that is at the heart of the Project's extraction and exploitation.

    Please do

    Don Marti: Insulating people from fake consent. Hard to pick which great section to excerpt, so I'll just give you the bottom lines:

    Some folk privacy practices are ineffective or out of date, but coming up with some way to “get this annoying banner out of my face” is a solid basis to build on.
    But sites aren’t going to abandon their existing investment in fake consent unless they have to. Whatever people come up with to implement MyTerms is going to have to block fake consent too. The tinyMyTerms demo implementation of MyTerms uses an standard ad blocker, something that people need anyway and that most people in the USA already have.
    Doc’s call to action is at the bottom of that blog post so check it out.

    Long Wave Goodbye

    In radio, the longest waves go fartest along the ground. This is why the longwave band was so important in the early days of radio. France's national station on 162 kHz and Germany's on 153 kHz both covered all of Europe and beyond, for many decades. Both those are gone now. And soon the UK's own giant, Radio 4 on 198 kHz will also disappear. 

    But you can still listen to the last of it, if you like, on personal radios exposed on the Net. They're called SDRs, for Software Defined Radios. Nearly all use the same KiwiSDR software, and work the same ways. Go to https://rx.skywavelinux.com/, pick one of the markers, and listen around. (Some SDRs are better than others. Check out several.)

    Here is one in Skipsea on England's east coast, north of Hull:

    http://vy2hf.proxy.kiwisdr.com:8073/

    Enter 198 in LW (for longwave) or AM (which it is), and hear the last of the service. To get the best sound, you may have to adjust the width of the dial marker by pulling out the two green flanks of the central frequency on the radio's dial.

    I've also listened to Radio 4 on 198 over this SDR at night in Canada's Prince Edward Island: http://vy2hf.proxy.kiwisdr.com:8073/

    It's fun to listen to that one at night for AM stations in the Northeast US and eastern Canada.

    I was a devoted radio listener (and worked for a while on the station side) for most of my life. DXer too. But broadcasting is being eaten alive by podcasting on the talk side and streaming on the music side. What's left is What's On: the live stuff. Games. News. Church services. But not much else. It's a death march. Wrote about that here: https://doc.searls.com/2025/05/05/the-offing-of-whats-on/

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  • The First Source of Personal Intent

    Where and when The Intention Economy first appeared.

    The largest coming conflict in the new AI world is not the one between AI giants or the one between those giants and governments. It will be the conflict between containment and expansion of personal agency. On the side of containment are expanded surveillance, guesswork, and entrapment in walled corporate gardens. On the side of expansion are tools that serve self-knowledge and expression of personal intent in the marketplace, including the intent to enjoy personal privacy, and have that work for both customers and companies.

    On the containment side, personal intent is already inferred by corporate agents fed a constant diet of surveillance data. On the expansion side, personal intent will be expressed by personal agents—ones owned and operated by independent and self-sovereign human beings. In the long run, agents on both sides will work cooperatively to expand communication and economic activity. But that can only happen when mechanisms that assure trust are in place. We can’t have those while surveillance continues to pay, and personal privacy is what corporate “consent” systems allow. Which rounds to none, because the financial incentives all but require surveillance. And the norms are deeply entrenched.

    But it’s still early. The Digital Age has been with us for decades at most and will persist for centuries to come. AI as we know it today is much younger. We don’t yet have ways to estimate opportunity costs of keeping customers naked and exposed in corporate captivity, and milked constantly for personal data.

    I coined “The Intention Economy” in a 2006 column with that title. That same year, I started ProjectVRM at Harvard’s Berkman (now Berkman Klein) Center. My book The Intention Economy: When Customers Take Charge (Harvard Business Review Press, 2012) posited a future described this way:

    Over the coming years customers will be emancipated from systems built to control them. They will become free and independent actors in the marketplace, equipped to tell vendors what they want, how they want it, where and when—even how much they’d like to pay—outside of any vendor’s system of customer control…

    Demand will no longer be expressed only in the forms of cash, collective appetites, or the inferences of crunched data over which the individual has little or no control. Demand will be personal. This means customers will be in charge of personal information they share with all parties, including vendors.

    Customers will have their own means for storing and sharing their own data, and their own tools for engaging with vendors and other parties…

    Thus relationship management will go both ways. Just as vendors today are able to manage relationships with customers and third parties, customers tomorrow will be able to manage relationships with vendors and fourth parties, which are companies that serve as agents of customer demand, from the customer’s side of the marketplace.

    Relationships between customers and vendors will be voluntary and genuine, with loyalty anchored in mutual respect and concern, rather than coercion…

    Likewise, rather than guessing what might get the attention of consumers—or what might “drive” them like cattle—vendors will respond to actual intentions of customers. Once customers’ expressions of intent become abundant and clear, the range of economic interplay between supply and demand will widen, and its sum will increase. The result we will call the Intention Economy…

    The volume, variety and relevance of information coming from customers in the Intention Economy will strip the gears of systems built for controlling customer behavior, or for limiting customer input. The quality of that information will also obsolete or re-purpose the guesswork mills of marketing, fed by crumb-trails of data shed by customers’ mobile gear and Web browsers. “Mining” of customer data will still be useful to vendors, though less so than intention-based data provided directly by customers.

    In economic terms, there will be high opportunity costs for vendors that ignore useful signaling coming from customers. There will also be high opportunity gains for companies that take advantage of growing customer independence and empowerment.

    The Intention Economy inspired Sir Tim Berners-Lee’s Solid Project, Consumer Reports‘ Permission Slip, work on personal AI at Kwaai.ai (which I serve as Chief Intention Officer)—among the many other efforts listed by ProjectVRM, which is still active. You can follow and join here.

    While tools for independent personal agency are still in their infancy, the corporate side imagines that personal intent is best inferred and controlled by companies, rather than expressed directly by customers and their own damn agents. As both sides muddle toward convergence in their own ways, are there middle grounds to explore?

    Shuwei Fang of Reuters and the Harvard Kennedy School is looking into that space. In The information ecosystem is being redrawn by AI, she writes,

    3. From artefacts to liquid information
    Once machines are the primary audience, the artefacts we have built around information (the article, the bulletin, the documentary) become structurally optional.
    Fragmentation was the old problem. Now information can exist without a container at all. And when information becomes liquid, the market bifurcates. Economic value concentrates at two extremes of a ‘barbell’; premium brands competing on differentiation and direct audience relationships; and commodity infrastructure operating at massive scale and razor thin margins. The middle, where most publishers currently sit, hollows out.
    4. From attention to intention
    When content is liquid and an intermediary controls the interface, something more consequential than format changes. The currency does. Clicks, pageviews, time on site; these were always crude proxies for what we actually wanted to know: what do people need? Now there are systems that can infer the answer directly. I have written elsewhere about this shift from attention to intention as the defining transition of this era.

    Good points. Now, what about systems that start with individual customers and their agency, their intent?

    Shuwei’s linked piece, From Attention Merchants to Intention Architects: The invisible infrastructure reshaping human curiosity, has this paragraph:

    Researchers are beginning to document the foundations of this phenomenon, what some at Harvard Data Science Review and elsewhere call the ‘intention economy,’ where AI systems collect, commodify, and potentially manipulate user intent. But this only scratches the surface. What they’re witnessing is accompanied with a fundamental restructuring in how information flows through society. In the intention economy now emerging, AI systems could compete to anticipate and shape what those eyeballs seek before they even know they’re seeking it. The infrastructure being built right now, largely invisible to most of us, won’t just determine what we see; it will determine what we want to see before we know we want it.

    The first link in that paragraph goes to a piece in December 2024that hijacked the meaning of intention economy. I tried to pull it back with The Real Intention Economy, and I’m doing the same here. I hope Shuwei reads it. The book too.

    Meanwhile, let’s get back to Shuwei’s From Attention Merchants to Intention Architects: The invisible infrastructure reshaping human curiosity, which concludes,

    But here’s what gives me hope: patient capital and policymakers are beginning to recognize infrastructure as the leverage point. The standards aren’t set yet. The architecture remains fluid. If these signals are correct, we might be at a rare moment where we can see a paradigm shift coming. Unlike previous shifts that caught democracy off guard (radio’s consolidation, television’s commercialization, social media’s polarization) we might actually have warning this time. If curiosity is becoming the new scarcity, if intention shapes outcomes more than attention ever could, then whoever builds the curiosity infrastructure could write the future of human understanding. And unlike attention, which is zero-sum and depletable, curiosity can grow through exercise, each question potentially spawning new questions, expanding rather than exhausting with use. This offers hope: the right infrastructure could create abundant understanding where the attention economy leveraged scarcity.

    For centuries, democracy fought for the right to know; freedom of information, transparency, the end of censorship. If AI makes all information instantly accessible, we might face a new frontier: ensuring the courage to question survives the comfort of infinite answers. The intention economy might not be inevitable, it could be a design space waiting for architects. The question isn’t whether we’ll have curiosity infrastructure, we probably will. The question is whether we’ll build it to expand human wonder or contract it.

    Indeed.

    To expand human wonder, we need Personal AI, not just the mainframe kind we have now. And within personal AI, we need mechanisms that enable and express far more personal agency than can ever be provided through the kinds of conversations we have today with Big AI.

    For full personal agency to thrive, we must have personal privacy. Because what we—the people—don’t say, and keep to our own private selves, may be far more meaningful and leveraged than anything that leaks out through AI queries. For that, we can start with contractual agreements such as those outlined by MyTerms (IEEE 7012).

    We will indeed use AI agents to express our intentions (including the one to be left alone). But they will be our agents, not ones fed by surveillance.

    We’ve been waiting eighteen years for those agents to arrive. It may take another one, three, five, or twenty years for that to happen. But it will.

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  • Ursday

    Random:

    Lidar all kinds of stuff.

    Two books:

    1. The Sovereign Human: Who Are You When AI Can Do Everything?
    2. American Trickster: The Hidden Lives of Carlos Castaneda

    Unpacked

    Apple Intelligence Foundation Language Models: 

    We present foundation language models developed to power Apple Intelligence features, including a ~3 billion parameter model designed to run efficiently on devices and a large server-based language model designed for Private Cloud Compute. These models are designed to perform a wide range of tasks efficiently, accurately, and responsibly. This report describes the model architecture, the data used to train the model, the training process, how the models are optimized for inference, and the evaluation results. We highlight our focus on Responsible AI and how the principles are applied throughout the model development.

    The list of authors is longer than that summary.

  • Whensday

    Just one of many windows like this today.

    Security at one cost: your time.

    A thousand years ago, there was a cooking show on TV called Chef Tell (real name: Paul Friedman Erhardt). My teenage kids and I enjoyed watching him for just four words he would say, after making something too complex for any of us to bother with. In his thick German accent, he would say “Vewy simple, vewy ee-see.” When, again, it was not. So whenever something complicated needed to be done, one of us would say, “Vewy simple, vewy ee-see.”

    I bring this up because I want tech support to be like Chef Tell. For example, today, when I mostly failed to solve an email problem. What follows is a diary of what I’ve been through on this thing.

    The primary email app on my laptop (a 2023 M2 MacBook Pro) is Apple’s Mail.app. It’s not ideal, but I like it better than Thunderbird and Outlook. I use it for five email accounts: my main one with Searls.com, my gmail one for Google stuff one can’t avoid, the Apple one a customer gets anyway (actually three, ending in .me, .mac, and .icloud), my Indiana University one, and a new one just for MyTerms stuff. That last one is hosted by Fastmail.

    So one day the MyTerms email account on Fastmail account stopped working. The password and login work fine with the Fastmail app, and with Fastmail’s webmail on a browser. But not with the Mac app. Working with our MyTerms.info admin person, I generated and tried some number of new passwords, made sure the logins, the TLS, and the ports were all correct. No soap. So we concluded, at least provisionally, that the problem must be with Apple’s Mail.app.  I then spent most of this afternoon on three calls with AppleCare, not taking to one human being. Apple seems to have nothing but AI agents now. (Not true, but I’ll cover that in another post.) The final advice from the final robot was to contact Fastmail.

    For guidance toward that, I went to the Fastmail app, and saw an email from Fastmail. It said,

    The above login failed because your regular password doesn’t work with third-party apps. This keeps your account secure. Instead, you can make a unique app password to use your account with the app securely.
    Your regular password can be used to create new users, change your settings, or cancel your account. It’s important to protect this, which is why it can only be used to log in to fastmail.com and the Fastmail app.
    We offer setup guides for most popular e-mail clients, such as Outlook and Mac Mail. These will take you through making an app password and using it for client login, step-by-step. Go to Settings → Migration to get started with a guide.

    The first link there took me to a page that says.

    Every third-party program or app needs its own app password to access your information. For the Fastmail app, you need to use your normal password. If you use your normal password or your Fastmail two-step verification password on an external account, syncing to an external service won’t work and you will see a password error.

    This led me into a maze of instructions for setting up two-factor authentication that required an authenticator app on my phone. Fortunately, I know what that is, because Indiana University requires the one called Duo for doing the two-factor dance with its email maze.

    After I got Duo set up, I still didn’t have an app password. I found a clue for that on another page that said this (among much else):

    If your app password is for an Apple device running iOS 11+, you can use the QR code to automatically set up your email on your mobile device. Please note that the link provided via the QR code can only be opened via the Safari browser. Through Safari, you should then be able to download the auto-configuration file to your device. Our Help Center has help pages with more information on Apple auto-configuration for based on your device’s iOS.

    The help page opens on every app I have other than Safari.

    Under Automatic setup tool on one of the Fastmail help pages, it has nine steps one must go through. Somewhere in there, I got to the New App Password page, where it said, under Setting up this Mac,

    Open this configuration file to set up everything automatically. Learn more.

    I clicked on the “Open this configuration file” link, which downloaded a file to my downloads folder. Clicking on it brought up a little window that said,

    **Profile downloaded.
    **Review the profile in System Settings if you want to install it. [OK]

    I hit OK. But where would it be in System Settings? Digging around in Fastmail, something said I would find the profile in General—>Device Management.

    It was there. Among other things, it said “Double-click to review.” This brought up a window that said Are you sure you want to install this profile? So I hit “Install…” and it seemed done. Above it, next to “Work or School Account,” a button said “Sign In…”. This brought up a window that said Sign in to a Work or School Account. Above my email it said “Your email address will be sent to Apple to check device management enrollment eligibility.” In blue,  it said “Learm more about device management…” Clicking on that brought up a window with a lot of words that I got rid of by hitting OK, so I was back to the last window, where there were buttons for Cancel and Continue. I hit Continue.

    This got me to

    Sign in with your managed Apple Account.
    Enter the password for your Apple Account (the email address) provided to you by your organization.”

    The password was back at my Fastmail app, under “Your new password for Apple Mail.app is::”

    I copied it and pasted in the field in the Sign in window and hit Next. This turned the window into a wider one that said, in red,

    Your Apple Account does not support the expected services on this device. Contact your administrator to sign in.

    My administrator is in London., where it is now 1am.

    I’m giving up now.

    Lost patience rates may apply

    One of the biggest reasons I own Apple stuff is that AppleCare seems to care. They have human beings for that. I’ve been using them since the service first showed up in 2001, along with Apple Stores and their Genius Bars. The agents on phones have always been helpful. They differed a lot in levels of expertise, but on the whole were very good.

    But now I only get AI agents. This has led me to wonder if they are replacing humans with AI agents. But I don’t know. They are recruiting service and support people. But not for front-line triage work, they’re using AI agents. Interesting that every one has a different voice. And in some cases they have been helpful. But not today. The one time the AI agent said they would forward my call to a person, I got about a minute of silence and then the call dropped. An Apple robot did call back, but I had given up at that piont.

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  • Draftday

    The NBA draft is tonight, and will be hugely interesting for fans, because this year's class coming out of college is unusually thick with talent.

    But what's happening with trades is more interesting to me right now.

    The Miami Heat just traded most of its team and some valuable future draft choices to the Milwaukee Bucks for Giannis Antetakuompo and Bobby Portis. Among the traded Miami players are Kel'el Ware and Kasparas Jakučionis, both of whom I got to see play in games here at Indiana University. Ware was on the Hoosiers, our home team. Jakučionis was on the Illinois Fighting Ilini. I saw one game in which Ware did not miss a single shot, including threes, and ruled the floor. And I saw Jakučionis pick apart the Hoosiers defense. They're both very good, with high ceilings.

    Giannis is a near-perfect basketball player, with enormous size, muscularity, and court smarts. He is also 32 (almost elderly for a big guy) and has been injured a lot in recent years. That's the biggest risk for Miami.

    The putative losers in this trade were the Boston Celtics, which were prepared to trade Jaylen Brown and some other players and/or draft picks to Milwaukee. This was never a good deal for Boston. In fact, I would hope that Brad Stevens, the General Manager, was only responding to outreach by Milwaukee rather than shopping Jaylen Brown, who has done nothing but improve through his ten years with the team. He has also been All-NBA multiple times, won a championship as the MVP, and was sixth this year in league MVP voting. The only thing arguing against him is that he said some unwise (and I think completely misunderstood) shit on a twitch stream. And now some of the talk on the sports podcasts is about how Jaylen is miffed that he was offered in trade at all. But this has happened before, and he knows the only way he'll be traded is if they get more back. I don't see that happening.

    Boston also has a great team. The only better ones, as it stands now, are the San Antonio Spurs, the Oklahoma City Thunder, and the New York Knicks. Odds-makers currently place the Celtics third, behind the Thunder and the Spurs, to win the title in 2027. They place the Knicks fourth, which is nuts.

    I put the Knicks first, because they are the best team. By far. The way they dominated the championship playoffs this year was a nonstop demonstration of how great teams win games that great players alone cannot.

    I hope for the sake of both the Knicks and the Celtics, and their longtime rivalry, that they both keep their rosters intact.

  • Where Apple Mail hides ‘All Sent’ in Tahoe

    Screenshot

    My wife’s Mac laptop has ‘All Sent’ listed under ‘Favorites’ in the left panel of her Apple Mail app. Everywhere my Big AIs and I looked online, however, we didn’t see a way to add it, until ChatGPT suggested I mouse over the Favorites heading to see what appears. The two items that showed up were a folder icon next to a down (v-shaped) symbol for collapsing the list below. When I clicked on the folder icon, I got the window above. ‘All Sent’ was among the choices under the pop-down menu. When I clicked on that, it was added to my Favorites and grayed out in the menu. So now this small instruction is out there for search engines to find and for the AIs to notice as well. Hope it helps other people looking for the same thing.

    BTW, there were other choices above On My Mac in the menu above, but they were all personal items I don’t want to share. The point is still clear.

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  • Toothday

    #2 is the one extracted today. It will get replaced. Same happened with #6 a few years ago. #17 broke, got yanked out, and is a blank space now.

    Something not to chew on. Or with.

    To dentists, teeth have numbers. They start on the top right, so your wisdom tooth there is #1. The numbers continue around to #16: your left wisdom tooth, then down to #17 below, and around to #32, your right bottom wisdom tooth.

    I’m losing #2 today at 1pm. It feels fine, because it is dead: had a root canal a couple weeks ago. Turns out it’s kinda rotted, though, and will get worse. The rot is too low for a crown, so it has to go. The plan is to go for an implant after the wound heals. Meanwhile, a gap.

    [Later…] First, my surgeon is a Starr, in more ways than one.

    It took longer and was more complicated than I expected, mostly because I’m opting for a replacement tooth, rather than a gap or a bridge.

    During prep, the nurse told me that fresh “bone matter” would be packed into the root cavities. The idea is that my skull will adopt the bone matter, make it my own, become skull, and then support the post that will be drilled into a solid mix of new and old bone. A new fake tooth will be emplaced on the post about nine months from now. In the meantime, I will chew on one side and mostly gum on the other.

    “Where does this bone matter come from?” I asked the nurse.

    “Cadavers,” she replied, adding that some corpse’s bone bits may escape from spaces between the stitches from time to time. Swallow it, and I’m a cannibal.

    Also, no solids for several weeks. Also yum.

    In the meantime, I have pain, addressed by my first opiates since getting my hip replaced eleven years ago. I’m not a fan, but we deal. Wish me sleep.

  • Fathersday

    Any will do

    I can’t call mine on Father’s Day. Pop died in 1979, eight years younger than I am now. Were he alive today, he’d be 117 years old. I only knew him for 32 years, but I can still hear his voice clearly, and would know it anywhere. Mom‘s too. And Grandma’s. Maybe I’ll hear them all before my end comes. That possibility is suggested by The profound meaning and mystery of deathbed visions, in Friday’s Washington Post. If you can get past the paywall, it’s a good read. Also, call a dad today.

    So now’s the time

    Buying a Used iPhone Makes More Sense Than Ever, Wired says. New ones are going to be more expensive soon (says The Wall Street Journal, and old ones are mostly just fine. Unless you’re doing fine-art photography or video, the differences between an iPhone 13 and everything since are not huge. I stuck with an iPhone 11 until the battery was crap and I got a 16. My wife got her iPhone 16 after her iPhone 6 finally died. The next iOS version, 27, will work on every iPhone going back to the 11. Naturally, markets being what they are, used iPhone prices will soon start going up too.

    The message in the medium called AI is in its first name

    Here is something I wrote yesterday in The George Carlin Model of AI, and just took out:

    Worse, Big AI is a giant digestive tract, extracting value from all the stuff in the world, hoovered up so its giant brain can make faked-up answers to anyone’s questions, make faked-up writing, faked-up code, faked-up music, faked-up art. It can fake all kinds of human output that does not require a human body. Lots of that shit is useful, helpful, and hell, amazing. (I use it every day.) But it’s not our shit, even though it can serve a zillion prosthetic purposes.

    That leveraged what we might call the Carlin Paradox: “Ever notice that all your shit is stuff and everyone else’s stuff is shit?” I thought that paragraph veered away from the thrust of the post, so I relocated it here, so I could tee up the headline of this post within a post.

    Bonus link from Charley Johnson.

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  • The George Carlin Model of AI

    Forty-five years ago, George Carlin forecast the future of AI:

    Listen to what George says, if you haven’t already. You can stop about two and a half minutes in, after he talks about how all your shit is stuff and everyone else’s stuff is shit. Because that’s the reason Big AI will never be personal AI. Big AI is not a place for your stuff. It’s a place that’s full of everyone’ else’s stuff. And yours too, probably.

    But it should be clear by now that we need AI. It’s too useful not to use, especially to make sense of our stuff. Which is what?

    A couple of years ago, I asked ChatGPT to generate an image of a woman having her own AI for her collection of stuff. I gave ChatGPT some categories for that stuff. The result was the image below. This was in the Olde Days of AI, when ChatGPT hadn’t yet learned to spell. So I added the words using Photoshop:

    Interesting that ChatGPT thought the place for her stuff was a coffee cup. But at least it was a physical thing. In reality, what would that physical thing be?

    Apple gave us the first model for one, back in the late ’80s. It was called the Knowledge Navigator:

    Hats off to Tor Hagemann for pointing us to it. Really, check it out. The video is less than six minutes long and describes the kind of thing we need: A device, not just a service.

    The place in that video is a professor’s study. For you and me, it might be a workshop or a cabin. Whatever the metaphor, we need a home on the Internet range: one as comfortable, safe, secure, familiar, and as much ours as our home in the natural world.

    Our digital stuff (such as in the graphic above) is what techies call “unstructured.” It’s many different kinds of data, organized in many different ways. AI is good at dealing with unstructured digital stuff. We just don’t have AIs of our own yet, or a place for our digital stuff. But work is going on. Let’s review some.

    1. Personal AI

    Here’s a picture worth many more words, from the company’s Platform page:

    2. Jan.ai

    “Personal Intelligence that answers only to you.” It runs on one’s own machine, with local models of your own choice, privacy by default, and a cloud option. Here’s a grab from the website today:

    3. OpenClaw

    Here’s what its Github site says:

    OpenClaw is a personal AI assistant you run on your own devices. It answers you on the channels you already use. It can speak and listen on macOS/iOS/Android, and can render a live Canvas you control. The Gateway is just the control plane — the product is the assistant.

    If you want a personal, single-user assistant that feels local, fast, and always-on, this is it.

    Supported channels include: WhatsApp, Telegram, Slack, Discord, Google Chat, Signal, iMessage, IRC, Microsoft Teams, Matrix, Feishu, LINE, Mattermost, Nextcloud Talk, Nostr, Synology Chat, Tlon, Twitch, Zalo, Zalo Personal, WeChat, QQ, WebChat.

    Website · Docs · Vision · Third-party notices · DeepWiki · Getting Started · Updating · Showcase · FAQ · Onboarding · Nix · Docker · Discord

    Lotta stuff there.

    4. Kwaai

    Kwaai is an nonprofit open source personal AI R&D shop with a large and active community. I volunteer there as Chief Intention Officer—a title that plays off The Intention Economy, which at least partly inspired the company. Kwaai’s main work these days is KwaaiNet, which its Github page describes this way:

    KwaaiNet is a decentralized AI node architecture for Layer 8 — the trust and intelligence layer above the traditional network stack — built by the Kwaai Foundation, a 501(c)(3) nonprofit AI lab focused on democratizing AI.

    Each KwaaiNet node combines:

    • A decentralized trust graph (cryptographic identity, verifiable credentials, local trust scores).
    • Shared, sharded LLM compute over heterogeneous CPUs/GPUs using Petals-style distributed inference. Apple Silicon Macs use llama.cpp with Metal for 30+ tok/s local inference; Linux nodes use CUDA-accelerated block sharding.
    • Secure multi-tenant knowledge storage via Virtual Private Knowledge (VPK) with encrypted vector search.
    • Intent-based, peer-to-peer networking that routes based on “what I need” (model, trust tier, latency), not just IP addresses.

    From an app’s point of view, KwaaiNet looks like a familiar chat-completion style HTTP API. Under the hood, it is a person-anchored Layer 8 fabric where every node is tied to an accountable human or organization.

    Companion Intelligence

    Companion Intelligence offers “the AI that you own.” Here are some more one-liners from the website:

    • “Stop renting the Cloud and start owning a personal AI powerhouse.”
    • “Your server. Your rules.”
    • “Digital Memory”
    • “A Local Home for Your Companion Memory”
    • “Your private AI cloud”
    • “Other agents are double agents.”

    Their place for your stuff is:

    • local hardware (a choice of their box or one of yours that you can turn into “your own unified private AI cluster”),
    • local storage,
    • local models or cloud models by choice,
    • persistent memory,
    • agents and apps,
    • remote access,
    • an app marketplace, and
    • wearable and browser inputs

    Companion Intelligence also has an interesting take on memory:

    Your life creates valuable context every day.

    It’s just spread across documents, notes, meetings, messages, and old decisions. Companion Intelligence brings that context together, so your agent can find what matters and help, more effectively, from where you left off.

    Most AI tools are temporary, and interchangeable. They answer a question, finish a task, and forget the larger story. Companion Intelligence gives AI a private home base: a place to understand your files, projects, routines, decisions, and history without making someone else’s cloud the center of your life.

    (For more on this angle, read Memory in the Age of AI Agents, by too many authors to list.)

    Agents for Companion Intelligence can come from elsewhere. They note two so far: Hermes and OpenClaw. They also promise “universal MCP Support for OpenCode, NanoClaw, Claude, Codex, VSCode & more.”

    6. Lovarys

    By offering you a server (actually a repurposed Mac Mini), Lovarys is similar to Companion Intelligence, but aiming for the professional market. Its tagline is “Professional Accounting and Legal Intelligence.” It’s a project of Tor Hagemann. Here’s his Github page.

    Around all of those efforts is an emerging ecosystem that (to me) seems to be trying to turn AI into an operating-system layer. Examples include:

    For more guidance on where this might go forward, here are two academic papers worth visiting:

    7. Apple

    This is the big one, and it just dropped a shoe the size of a continent:

    No, this isn’t it true personal AI yet. But it is beyond significant.

    Siri is Apple’s Clippy. Maybe worse, because it’s still alive and unloved after fifteen years of relentless promotion and disappointment. (Start reading down from the Reception subhead on Siri’s Wikipedia page for a partial account of Siri’s failings. A lot there.) But never mind that. Instead, mind these two words:

    Meaning private.

    Apple is huge on personal privacy. In case you’ you’ve missed Apple’s many ads and videos, you can get the gist of the company’s privacy case here, here, here, here, and here. A couple of years back, in response to the first of those, I wrote here and here about how Apple comes up short on the privacy front, despite its many promises. But I give it points for staying on the case, which will get a lot bigger with this next operating system.

    An aside:::: It’s hard to sell privacy when the person can’t easily tell whether or not they’ve been exploited or protected. Both happen mostly out of sight.

    Here’s a video in the style of a movie trailer, laying out Siri’s fancy new features. It’s annoying to watch (at least for me), but it’s a good tease.

    Will what Apple brings us in version 27 of iOS and MacOS at least start to give us a place for our stuff? A truly private place? Let’s look—

    1. On-Device “Personal Context”: A new architecture (not the old Siri) maps your device locally, using Apple Silicon’s Neural Engine to index information across your Apple applications: contacts, calendar, reminders, messages, emails, documents, photos. As for your non-Apple stuff, such as my million-plus photos that are not in Apple’s Photos app, it looks like it’s already on the case. When I search for “tunnel” across my photo directories with my laptop (2023 MacBook Pro running Tahoe 26.5.1), I get every shot where that word appears, plus lots of stuff that is either a tunnel or looks kind of like one. Example:

    Clearly an AI does some pattern recognition there, but is that “personal context”? I dunno,

    It has “Semantic Indexing,” which makes informed presumptions about the meaning of your data, and not just your keywords. Big AI does this now, but Siri will do it just for you, on your stuff, inside your place for it. Note what it says under the “Apple Intelligence in Apps” subhead here:

    Express yourself through photos and images, save time with Safari, and get more done with Apple Intelligence seamlessly integrated into your everyday apps and experiences.

    But do we want “seamless” everything? We need edges, boundaries, to make sense of the world. Right now I just want the option to turn that off, or not turn it on. Unless it’s the thing that sees tunnels. I don’t know, and that’s a problem.

    2. Private Cloud Compute (PCC) is how Apple describes another place for your stuff: kind of a private office in Apple’s hi-rise downtown. Specifics:

    For advanced features that need to reason over complex data with larger foundation models, we created Private Cloud Compute (PCC), a groundbreaking cloud intelligence system designed specifically for private AI processing. For the first time ever, Private Cloud Compute extends the industry-leading security and privacy of Apple devices into the cloud, making sure that personal user data sent to PCC isn’t accessible to anyone other than the user — not even to Apple. Built with custom Apple silicon and a hardened operating system designed for privacy, we believe PCC is the most advanced security architecture ever deployed for cloud AI compute at scale.

    The authors of that text are Apple Security Engineering and Architecture (SEAR), User Privacy, Core Operating Systems (Core OS), Services Engineering (ASE), and Machine Learning and AI (AIML)—all inside the company. They say lots more at that last link, all helpful to know. So is Expanding Private Cloud Compute, by the same teams.

    3. Systemwide app actions: This new assistant can, for example, cross-reference a tracking number from your email and a message thread to find who asked for it, pull out other relevant information, then automatically drop it into a reply for you to review or edit before you send it, all in your virtual cabin (device) or office (private cloud).

    4. Controlled federation, anonymized gateways, a privacy shrowd, and other jive required to make this work:

    From this press release.

    I gather, from Apple’s literature, that Siri strips out your IP address and personal identifiers before making a query to an external AI. The external AI agent sees only the isolated query. This prevents the external AI from examining the personal stuff in your online home.

    5. The Mac Mini, or some new dedicated place for your stuff.

    News items:

    Given all this news, I will be amazed (but not surprised) if Apple doesn’t push the next Mac Mini as the personal AI machine, meaning the place for your stuff.

    Okay, so here is a table of what we’ve reviewed so far:

    SystemOwnerMemoryOutside AIsSovereign?Character
    Apple IntelligenceApple/personDeepYesPartialPrivate cabin inside Apple’s estate
    Personal AICompany/personDeepLimitedPartialDigital twin in the cloud
    OpenClawPersonDeepYesMostlySelf-hosted AI stack
    Jan.aiPersonModerateYesMostlyPersonal AI workshop
    Companion IntelligencePersonDeepYesMostlyPersonal homestead
    LovarysProfessional/personDeepSelectiveMostlyPrivate study or office
    KwaaiPerson/communityIntended deepYesAspirationalCooperative village
    FriendCompanyModerateYesNoCompanion in somebody else’s house

    Here is a tough question: What if only a giant can put together most or all of what we need? Three giants currently furnish most of our personal spaces in the digital world:

    • Apple (iOS and MacOS devices, Safari browser, etc.)
    • Google (Android devices, Gemini, Chrome browser, etc.)
    • Microsoft (Windows OS and devices, apps, etc.)

    With iOS and MacOS 27, Apple moves to the front of that pack in the personal AI space, and will likely be the only giant to offer something that looks like a place for your stuff. Given its role in the surveillance fecosystem, Google can’t be trusted. Microsoft still has Micro in its name, but it has become much more of an enterprise company in recent years. So, among giants, Apple is it.

    Now let’s talk about agents.

    Apple sees you with just one: Siri, or whatever Apple lets you call it. But you will probably need many agents: one or more for health (in various specialties), financial (banking, investment, credit), travel (airlines, car rental, hotels), home economics (property, stuff in storage, scheduling the kids, keeping the car working), legal (all your contractual commitments, plus much better customer-company interactions than are possible today).

    This can get very complicated. As Opaque explains here,

    Here’s the thing: if a single chatbot request is too risky to run unverified, what does that say about agents?

    A chatbot is one request in, one answer out. An agent runs that risk in a loop: reading email, opening files, calling tools, handing work to other systems, unattended and at machine speed.

    No breach required. An agent doing exactly the job you gave it moves your data constantly into places you don’t control and mostly can’t see.

    Now wire thousands of agents together, the way every enterprise is planning to this year. Whatever the per-step risk is, compounding turns it into a certainty.

    Apple just deployed Confidential AI to protect the smallest risk surface in AI. Enterprises are wiring up the largest with nothing underneath it.

    Opaque doesn’t care about you or your “smallest risk surface in AI.” It sells arms to enterprises. But it does make a good point in its opening sentence:

    “Apple looked at a simple chatbot, the single most contained form of GenAI there is, and decided the data it leaks is too dangerous to ship to their customers without Confidential AI underneath it.”

    To Apple, the more personal the context, the higher the privacy stakes. That’s why it believes personal AI has to run—

    • on-device (the place for your stuff) and
    • in a privacy-walled cloud infrastructure (your private office in Apple’s high-rise cloud)

    The former can actually cover a lot of ground in your life, just by helping you get on top of all the stuff in your digital home. It can also handle some simple interactions with outside entities, such as MyTerms ceremonies and record-keeping.

    But you’ll need much more from your personal AI if you’re going to scale your life out into the larger world, where nearly every company, every government agency, everything you might subscribe to, and even every church and nonprofit, wants to have AI agents for interacting with the you and your digital agents.

    As of today, Apple isn’t ready for that. Nor is anyone else. But researchers are helping. In Too Private to Tell: Practical Token Theft Attacks on Apple Intelligence, four researchers from Ohio State University,say this in their abstract:

    Apple Intelligence is a generative AI (GenAI) service provided by Apple on its devices. While offering a similar set of features as other similar GenAI services, Apple Intelligence is claimed to be designed with an extra focus on user security and privacy through a two-stage authentication and authorization design using anonymous access tokens. In this paper, we present our investigation into this token issuance mechanism with a goal to reveal possible vulnerabilities using traffic analysis, reverse engineering, and cross comparison with Apple’s public documentation. Specifically, we present the Serpent attack, the first practical cross-device token replay attack against Apple Intelligence that allows the attacker to steal the access tokens from the victim’s device and utilise them on a different device, with all usage rate-limited against the victim. We have achieved successful attacks on the latest macOS 26 Tahoe and demonstrated that an attacker, who even has used up its own allowance, can immediately regain access to Apple Intelligence service. We have responsibly disclosed the vulnerabilities to the vendors and received confirmation from Apple with CVE assigned and bounty given. Our results highlight a general lesson for built-in AI services: Anonymising identity does not by itself make the AI service secure; Enforcing non-transferability requires cryptographic binding to the rightful user.

    We assume that Apple is addressing those concerns, plus a near-countless number of others, with MacOS 27 and iOS 27. We’ll see later this year, presumably. (Apple is better with promises and forecasts than most others, but not perfect.)

    Humans invented privacy with the technologies we call clothing and shelter. We don’t have clothing yet in the digital world, or we wouldn’t be walking worse-than-naked across the Net, covered with thousands of invisible data-sucking ticks called cookies and tracking beacons: parasites that report who-knows-what to god-knows-who, across thousands of unseen and unknown paths.

    But we might get shelter, or the beginning of a working model for it—a place for our stuff—from Apple and these other companies and projects.

    Apple seems to understand some of this, at least architecturally, to some degree. I think others (including those listed above) understand it more deeply. But none of them have Apple’s heft.

    As for the enterprise side of this, there are growing bodies of work coming from Nitin Badjatia, Iain Henderson, and Jamie Smith. All three see empowered customers coming to the marketplace with agentic AI capabilities that will strip the gears of existing enterprise systems, including those with AI agents.

    In Confidential AI Just Hit Escape Velocity (published on 13 June), Aaron Fulkerson, CEO of Opaque, writes this:

    Apple just set the bar every enterprise will be measured against

    Escape velocity is the moment a category stops needing evangelism, when the question flips from “do I really need this?” to “why don’t you have it?” Three things flipped it this month.

    First, the existence proof landed at the hardest difficulty setting. Apple just rolled out the largest Confidential AI deployment in history: every iPhone, at consumer latency, consumer cost, consumer scale. Every objection enterprises have leaned on, too slow, too expensive, more than we need, just got falsified a billion times over by a phone.

    Second, this is already how the giants operate. Meta runs WhatsApp message AI through private processing. Google built Private AI Compute so Gemini can process your personal data in a sealed environment that, in Google’s own words, not even Google can access. Anthropic and TikTok run their own implementations. And Microsoft, Google, and NVIDIA ship the underlying confidential infrastructure across their clouds and silicon. The pattern is consistent: every company with world-class security talent, when forced to put AI against sensitive data at scale, lands on the same architecture. When that many teams solve the same problem independently and arrive at one answer, you’re looking at convergence.

    On our side—the customer’s side—we need confidential personhood, based on personal sovereignty: root for the person. In other words, personal AI needs to be operated by the person, not just for the person.

    So let’s suppose Opaque succeeds perfectly. Enterprises will have attestable hardware, secure enclaves, confidential containers, encrypted memory, verifiable runtimes, machine-speed agents, and other whatevers we’ve been reading about.

    We will need the same. The flow should go like this:

    Natural person
        ↓
    Personal AI
        ↓
    Personal terms (MyTerms)
        ↓
    Confidential runtime
        ↓
    Outside agents and services
        ↓
    Network

    Note also that the flow here is top-down from the person, the individual—rather than bottom-up from “the consumer” or “the user.”

    Almost everybody talking about agentic AI today is looking only at the lower half. But that half won’t run without our permissions from the upper half. That’s why we (the working group I chaired) worked for nine years on  IEEE 7012-2025—Standard for Machine-Readable Personal Privacy Terms. Its nickname is MyTerms. As I say there, MyTerms is the only way we’ll get personal privacy in the digital world. Apple, please adopt it. Everyone else, jump on board too. It’s a radically simple to implement. From that last link:

    MyTerms are contractual agreements about personal privacy that you proffer as the first party, and the company agrees to as the second party. With MyTerms, you don’t “consent” to the company’s privacy policies or whatever they say about their use of cookies. They agree to your privacy requirements, which will limit the use of cookies and tracking tech to only what you allow. You are not a mere “user” or “client.” You are an independent human being operating with full agency.

    In a way, Aaron Fulkerson’s post argues a need for work on the upper half. Because, while he says, “the request never travels on trust,” our social and economic lives are based entirely on trust: contracts, promises, agreements, agency, representation, delegation.

    If my personal agent books a hotel, negotiates a subscription, grants limited use of my health data, tells my bank to move money, buys something, or participates in market intelligence that flows both ways, those acts and processes aren’t just computations and transactions. They are relationships. And those require identity, delegated authority, obligations, records, audit trails, and remedies. Those all need to start with My Terms.

    At scale, remedies must be based on ODR (online dispute resolution), which is thankfully a mature field.

    I suspect Apple, Opaque, and MyTerms are each solving a different problem posed by a place for my stu ff:

    LayerQuestionExample
    Confidential computingCan I trust the machine?Opaque, et. al.
    Personal contextDoes the machine know me?Apple, et. al.
    Personal sovereignty (confidential personhood)Does the machine represent me?MyTerms
    Dispute & accountabilityWhat happens when things go wrong?ODR

    In each case the place for my stuff is a machine. My (or your) machine, and possibly your private cloud. Nobody today is building that whole stack. Nor should anybody. Not if we want each layer to scale.

    So here is a question. What if:

    • Apple provides the shelter (then competitors follow),
    • Opaque (and its competitors) provides the locks,
    • Linux and open source hacks provide the plumbing, and
    • MyTerms provides the constitution—or at least a solid ground under a new constitution for personal agenc, independence, and privacy online?

    If personal AI becomes ubiquitous, agents will do things that matter legally and socially. The questions that matter then become, “Under whose authority?” and “How is that authority secured?”

    The answer to both require contracts in which the person is the first party. Fortunately, contract law is well established everywhere, and contract itself is specified by Article 6 of the GDPR as one the the lawful bases for others to process one’s personal data. (Dive deeper here if you like.)

    So, while we wait for Apple to drop the other giant shoe, let’s get its alternatives farther downstream, and start putting MyTerms to use. Our home—places for our stuff—on the Net won’t be secure without them.

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  • Ladderday

    Ed Zitron's latest two are good reads:

    I've worked in the Valley, both on-site and in the world, since 1977. (On site was '85 to '01.) It ain't the same. 

    On the contrary?::: Notebook LM does more stuff than ever.

    The always sensible Bruce Schneier: 

    New book coming soon: The Nerd Reich Is Coming, from Gil Durán of George Lakoff's FrameLab. Out August 18. I've pre-ordered it.

    Finally, in Nature (where else?), A squirrel-inspired drone with enhanced stability, agility and maneuverability via whole-body morphing.

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  • Wryday 

    And then repeats as champs

    Rumors have it that Giannis Antetokounmpo is headed for the Boston Celtics in a complicated trade that will send Celtics stalwart Jaylen Brown to Milwaukee or elsewhere. I doubt this will happen, simply because at this stage in their careers, Jaylen is a far more reliable player than Giannis. Sure, Giannis—The Greek Freak—is one of the greatest players of all time, and a lot bigger than Jaylen. But Giannis hasn’t stayed healthy for years, and is unlikely to ever return to peak form. Meanwhile, Jaylen is ridiculously well-conditioned, improves his strength and skills every year, and is two years younger than Giannis. The only thing arguing for a trade is that Boston has two very expensive players on max contracts: Jaylen Brown and Jayson Tatum, and Tatum is slightly better. This means the best the Celtics can do with those two players on the team is pack small contracts around them. The new model, thanks to the salary limits and extreme “luxury taxes” for exceeding them, is to have just one player on a max contract, and a bunch of less expensive players surrounding him. This is the Knicks’ model with Karl-Anthony Towns. Jalen Brunson famously took less money to make room for Towns, Bridges, and others. That’s why I expect the Knicks to stay cool while the rest of the league heats up around trades.

    Loose links

    UT Austin leadership fires KUT General Manager Debbie Hiott.

    BTW

    I had more on this post, but something got f’d up, and now it’s gone. But I won’t try to fix it. Gotta move on.

  • My Crowning Soccer Moment

    Imagine a thick crowd coming at you. Also a soccer ball.

    The only college sport I ever played was soccer, on the new club team my small college put together during my sophomore year. I only qualified because I showed up and didn’t suck at it. Two weeks after starting practice (which was fun and I loved), I got kicked off the team because the coach discovered I was on academic probation.

    But some skills don’t go away entirely, and that’s what mattered on an August day in 2015, at age 68, when I was limping slowly down the 184th Street tunnel (above) to the A train’s 181st Street station in New York. That’s the tunnel, above. At the far end, two guys were kicking a soccer ball back and forth, and didn’t stop when a thick crowd, fresh off a train headed uptown, filled the tunnel, moving in my direction.

    A few weeks earlier, I’d had my right hip replaced, and I was just beginning to become fully ambulatory. So I was hoping not to collide with the crowd—and that the ball would not find me. But it did. By reflex, I trapped it with my right (bad) foot, and then shot a perfect pass through the crowd to one of the two guys. After the crowd passed, the two guys came over and enthusiastically began talking to me in Spanish.

    I smiled, said “Muchas gracias,” and continued limping toward the train. But it felt good to enjoy a moment of apparent competence in a sport at which I was not yet entirely lame.

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  • Fewsday

    One frontier of anthropomorphism

    In the midst of a dialog with ChatGPT, I just got this: "Doc, I've been thinking about this off and on since your earlier questions…"

    Is it really thinking? Will it feel insulted or betrayed that I just blogged this? 

    Olds

    In the continuing story of news as a business, newspapers have been written out. The surviving characters are—

    1. Social networks, video networks, and AI
    2. News websites and apps
    3. TV

    Or so it says in News sites are the new newspapers: People are abandoning them for social media, by NiemanLab, which cites the 2026 Digital News Report from Oxford’s Reuters Institute for the Study of Journalism (RISJ). The RISJ has its own summary here.

    The news commons, if it ever does become a thing, fits in #2.

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  • Opday

    On a medical frontier

    Adrian Gropper in the AI corner of the New England Journal of Medicine: The Medical AI Assistant as Publication, Not Device — Why Peer-Reviewed, Open-Source AI Belongs in the Standard of Care. From the abstract: "I argue that when a physician publishes a MAIA’s architecture, retrieval methodology, and validation results in a peer-reviewed journal, the published MAIA enters the medical literature as any other clinical methodology would. Physicians who subsequently adopt this methodology are not operating a medical device — they are practicing medicine informed by the published literature."

    Can they both be right?

    Two opinions about SpaceX's stock worth. Keith Teare is bullish. Dana Blankenhorn is bearish.

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  • The Formerlies

    See Reason #10 below.

    This Knicks NBA championship run is the greatest of all time. Reasons:

    1. They won sixteen of nineteen games through the playoffs, including two sweeps. They only lost the first two games in the first round, each by one point, and then one game in the Finals by not much, and their city blames Trump for jinxing them for that last loss—one where his presence was hugely inconvenient and distracting, for which he was clearly not interested (except in self-aggrandizement), and during which he fell asleep.
    2. They are The Formerlies. Except for Mitchell Robinson and some benchwarmers, they were all acquired off the Used Player market. 
    3. They played in the East, considered the weaker conference, and won only 53 games in the regular season. Detroit, Boston, and Cleveland all won more. But the playoffs are clutch time, and nobody has ever been more clutch when it mattered most than these Knicks.
    4. They have no top-tier stars. Only Jalen Brunson is all-NBA, and he’s on the second team. They also have no “big two,” or “big three.” They have a big ten: Jalen Brunson, OG Anunoby, Josh Hart, Mikal Bridges. Karl-Anthony Towns, Miles McBride, Landry Shamet, Mitchell Robinson. Jordan Clarkson, and Jose Alvarado (in declining order of minutes played in the playoffs).
    5. They are best team of the modern era, exemplifying what Bill Simmons calls “the secret.” Specifically, “The secret of basketball is that it’s not about basketball.” It’s about players caring more for each other, and for the team, than for themselves. It helps that three players (Brunson, Hart, Bridges) won championships (plural!) at Villanova, and call each other “Brothers for life.” Watch them for a while, and it becomes clear that the team is like a family. It also helps that Rick Brunson, Jalen’s dad, is an assistant coach with the team, and that the coach, Mike Brown (another Formerly) seems more like an uncle. 
    6. In the playoffs, they became all but unbeatable. Losing is out of character for them. They could fall behind by any number of points, and their eventual victory still seemed inevitable. In the final game, when the Knicks were within seven points, it looked to me like the game was over already: the Knicks would close the gap, take the lead, and win. They know how to do that, over and over. They are glued, experienced, determined, and locked in. You can see the other team start to melt.
    7. Jalen Brunson, Captain Clutch, proved he was the real league MVP. By miles. None of his moves look especially slick or athletic, but he is so good at getting open, slipping past defenders, shooting fallbacks, and getting layups no matter what, that it’s crazy to think the guy is just 6’1″ (okay, with a 6’4″ wingspan) with no shoes on. He is a great leader, an unselfish teammate, and very dependable in the clutch. OMG, and tough. I just heard Bill Simmons call Brunson the toughest guy in the league. Who’s tougher?
    8. In the Finals, they beat the best collection of players in the league, starting with Victor Wembanyama, who will likely go down as the greatest player of all time if he stays healthy, learns from his failings, and wins a bunch of rings. 
    9. New York showed it’s the Greatest City in the World. You could feel the love the team and the city have for each other. I grew up a Knicks fan in New Jersey, across the river from New York. Used to go to Knicks games for $5 a ticket, many decades ago. But I’ve also spent a lot of time in Boston, San Francisco (where I had season tickets to the Warriors), and Los Angeles. Among major cities, only Boston compares to New York for the level of civic devotion to the team. Both also share a subway culture, which heats up fandom, heart-to-heart, despite all other differences. But New York is a lot bigger. (And yes, San Antonio is a great basketball town too. But it’s a town. A great town. But not New Yawk.)
    10. The Knicks victory was great for basketball. This year’s Finals was hugely popular. Ratings across the four-game series averaged 19.6 million viewers, +116% over 9.1 million for last year’s Thunder-Pacers series. This was the most-watched Finals in the current millennium. There was also a spike in younger demographics. Viewing among teens (12-17) jumped by 138%, and young adults (18-24) spiked with 147% compared to last year.

    All this is debatable, of course. Just not right now.

  • Shunday

    Other laws may apply

    I started to write something here, but turned it in to a whole post on its own: Customer Service Sample of One. In response to that, Don Marti pointed to Skylabs Audio and its YouTube channel. As it happens I was an audiophile many decades ago. Worked weekends at an audio salon in Chapel Hill. Had some good gear, all bought cheap or built from a kit. Anyway, I got over all that stuff long ago, but I still care a little.

    But mainly I live in the now, when things are a lot more complicated, and customer service is kind of a ballet in which both customers and companies dance with a character named Murphy.

    Edit

    I moved my Knicks post to its own page, titled The Formerlies.

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