Regulating AI won't protect Americans; it's about Big Tech having a monopoly



The more I read and write about AI, the firmer I get in my conviction that Big Tech incumbents absolutely must strangle the decentralized AI in its cradle before it wrecks everything.

Take a look at this interview Ben Thompson did with OpenAI’s Sam Altman and Microsoft CTO Kevin Scott. I call your attention to this part in particular:

From Microsoft’s perspective, is this going to be a funnel into new products or do you see it as an end goal in and of itself, winning search?
KS: So I think you hit on a very important point which is even if the ad economics of this system doesn’t have the same economics that “normal search” has, if we gain share, it’s just great for Microsoft. I think we have a lot of ability here, partially because we’ve done so much performance optimization work and we’re really confident around costs, that we can figure out what the business model is. The thing that I know having been a pre-IPO employee at Google is the search business that you have now is very different from the search business that we had twenty years ago, and so I really think we’re going to figure out what the ad units are, we will figure out what the business model is, and we have plenty of ability to do all of that profitably at Microsoft.
SA: There’s so much value here, it’s inconceivable to me that we can’t figure out how to ring the cash register on it. [Emphasis added]

I recently said the same thing to an interviewer who asked me about search and Google. The point I made was that Google was here before with search the first time — there was no business model for it until it hit on one (by acquisition, no less). Don’t assume, I argued, that it won’t hit on another profitable model for whatever kind of user experience BingGPT and Bard evolve into.

But I also made another point to the interviewer that’s not at all captured in the above but that’s critically important for everyone thinking about tech policy in the current moment: to make any business model work for them, they will first have to kill decentralized AI.

Centralized vs. decentralized

There’s a set of assumptions implicit in Scott and Altman’s vision of how they might eventually “ring the cash register” on AI-backed chat as the new query interface for most information:

  • Users go to their centralized servers and type text into a box that they host.
  • Advertisers go to those same servers to get in front of all the users.
  • Somehow, the advertisers and the users can be connected to one another, with Microsoft acting as a middleman.
  • Or, maybe the users pay Microsoft directly for the queries via a subscription or micropayment scheme.

In other words, Microsoft’s ability to squeeze profits out of the experience of interacting with an LLM presumes that billions of users will continue to flock to a handful of centralized services to get their queries answered. This is a vision, then, predicated on a world of centralized AI.

But what if we end up in a world of decentralized AI instead? What if I can download an app that will answer current questions from all of Wikipedia and Reddit, in some cases going out to both of those sites and pulling in fresh data?

What if some of the data sources are my favorite news websites and forums, all of which have signed up to provide data to the app and which get a cut of whatever revenue it generates?

Or, what if multiple such apps are powered by open-source language models and kept fresh by access to current data sources via an API? I could certainly see the New York Times publishing such an app all by itself, with the ability to answer any question from its vast archives of past issues.

Decentralized AI is a real threat

To give some technical context for why the vision of app-based, decentralized AI I’ve described above is quite possible, consider that the size of the models needed to do this might be on the order of a few gigabytes each. For instance, the Stable Diffusion model file that powers its image generation is from 2.5 to 4.5 GB, depending on the version, and it was trained on 240TB of image data. That’s an astonishing level of compression.

So, it may be possible that the average size of the models that we need to answer, say, 75% of our random questions about the world is roughly 3GB or so — about the size of a large mobile game download.

If I can download models that can reliably answer questions about their training data, why do I need to visit a Microsoft- or Google-hosted website and type queries into their text boxes? If I want recipes from my favorite recipe site, maybe I visit their site instead and talk to their model. If I want the current NYT or WaPo consensus on Ukraine, why won’t I just go to those sites and chat with their bots? Why does a Microsoft or a Google need to be involved in any of this?

The answer, of course, is that they don’t need to be involved. Decentralized AI can and will cut them out entirely, assuming it’s allowed to.

But that’s a big assumption because the future of decentralized AI is by no means guaranteed.

But before we go into who’s trying to kill decentralized AI and why, some caveats:

  1. Using the models to answer questions requires quite a bit of computing power. But these inference costs can and will be reduced with innovation, as this is an active area of research. Also, have you seen mobile phones, lately? There’s no shortage of computing power, and phone makers are always looking for ways to use it. After a few product cycles of optimizing the hardware for running queries, it’s not hard to imagine very fast local performance on many kinds of models.
  2. Yes, the models still make up facts. This hallucination is a big problem, but it’s also one that everyone is working on. The models will get better at faithfully representing the facts in their data sources.

We’ll have to fight for a decentralized future

I’ve written at length on my Substack about the forces arrayed against decentralized AI, so I won’t repeat that here. But to summarize: The aforementioned model files representing the “brains” of an AI like Stable Diffusion or ChatGPT could very easily be treated like digital contraband and wiped from the internet.

Everyone from Googlers to Google-hating former Googlers to indie artists to profiteering lawyers are hard at work constructing rationales for why these model files should be subject to the same censorship as child porn, 3D-printed gun files, pirated movies, SPAM, and malware.

Here are some of the rationales currently being explored for banning decentralized AI:

  • All the model files are full of copyright violations because they were trained on copyrighted data.
  • Generative text models can cause harm to the marginalized because “hate speech” can be coaxed out of them.
  • Generative text models will catastrophically increase the threat of “disinformation.”
  • Generative image models will be used for non-consensual fake porn of real people, many of them children.

We wouldn’t even have to pass any new laws to have these model files banned. All it would take was an agreement among a handful of large players that these files and any apps or sites based on them pose a threat. I imagine the following platforms can and probably will come together to effect what amounts to an effective ban on decentralized AI:

  • Google Play
  • Apple’s App Stores
  • Amazon Web Services
  • Cloudflare

This means a world where everyone gets to host their own models backed by their own data sources, and facts are by no means guaranteed. Going by the lessons of history, I’d say it’s probably unlikely.

It seems increasingly likely to me that the forces of centralization will succeed in getting unauthorized model files treated like contraband, and in five years, we’ll still be running all of our queries on servers hosted by one of the Big Tech platforms.

I hope I’m wrong about this, but I do know that if we’re going to have decentralized AI, then we’re going to have to fight for it.

How Google’s getting an AI backdoor into iPhone



Apple and Google have long held differing views on user data and device privacy. While Apple promises to keep most personal info on-device and encrypted, Google is known for mining user data and leveraging it to serve ads, improve products, and more. However, a new partnership between these two tech giants could allow Google’s AI platform, Gemini, to access user data like never before.

If you can’t beat them, join them

Earlier this year, rumors swirled that Apple was working on a new AI-powered version of Siri for iOS 18. The update would make Apple’s personal assistant comparable to generative AI platforms like ChatGPT and Google Gemini, allowing it to provide better query responses, edit written content, and possibly even create text and images of its own. While this project may still be in development, new details claim that Apple hopes to kickstart its AI ambitions by striking a deal directly with one of its competitors.

Google Gemini is now poised to take center stage at Apple’s WWDC event this spring, where iOS 18 is expected to be unveiled. Debuting in December 2023, the platform is relatively young compared to OpenAI’s ChatGPT, which launched to the public in November 2022. However, Google has been quick to iterate on the platform as it aims to replace its antiquated Google Assistant soon.

Apple and Google go back farther than you think

This isn’t the first time Apple has let Google into the iPhone. For instance, when the iPhone debuted in 2007, Google Maps was the default navigation app that came pre-installed on every device. This would remain the status quo for iPhone users until Apple Maps swooped in as a homegrown replacement in 2012.

YouTube was also famously built directly into the iPhone until meeting its untimely ousting for reasons unknown in the same year. Google took the gesture in stride by launching its third-party YouTube app on the App Store today.

Despite Google missing out on some direct integration with the iPhone, the search giant reportedly pays Apple $18 billion per year to be the default search engine in Apple’s Safari web browser across all Apple devices, including iPhone, iPad, and Mac.

The two tech giants have a history of working together, significantly when both businesses can mutually benefit from one another and Apple’s rich user base. In the case of Gemini, Apple gets to boast new AI features on the iPhone that weren’t possible before. Google gets instant access to a larger pool of users, which could help it supplant ChatGPT as the leading generative AI solution on the block.

How does Google Gemini work?

While it’s a mystery how Gemini will be integrated directly into iOS 18, it’s possible to interact with Gemini today through your web browser. Simply go to the official Google Gemini website and sign in with a Google account. Before you do anything else, note the disclaimer at the bottom of the page:

“Your conversations are processed by human reviewers to improve the technologies powering Gemini Apps. Don’t enter anything you wouldn’t want reviewed or used.”

Keep in mind that live Google employees will review anything and everything you type into the prompt bar. Why? Because Gemini is still in the early stages of development, and Google’s employees are continuously monitoring the platform and making changes as issues arise, like with the diversity image scandal in February.

But even once Gemini has surpassed the need for human reviewers, you should still know that every request typed into the prompt bar is sent to Google’s servers to be processed before all responses can be sent back to your device. This means that Google will still technically have a record of every request you make and every response it creates on your behalf for up to three years, according to Google’s privacy policy.

So, be careful what you say to Gemini, especially if you value your privacy.

What does this mean for user privacy?

Herein lies the tricky part of this collaboration between Apple and Google. How does the former, which prides itself on user privacy and keeping as much data on-device as possible, work with the latter that regularly collects and processes user data through its servers in the cloud?

It’s hard to believe Apple would be willing to compromise its privacy-focused values just to add generative AI capabilities to its devices, and it might not have to. Google makes a version of Gemini called Gemini Nano that’s small enough to run directly on-device without sending user data to Google’s servers. This module is currently reserved only for Google’s Android-powered Pixel 8 Pro and Samsung’s S24 series, but any device that supports Android’s AICore system could technically run Gemini Nano.

Then again, the only way to get the most advanced features Gemini offers is through leveraging Google’s much larger and far more powerful AI models located in its cloud-based servers. Whether or not this extra power is worth the potential privacy trade-offs is up to Apple. However, if the company is willing to expose users to Google’s data-tracking efforts through Safari, giving up data to Gemini isn’t much of a stretch.

Regardless of how Google Gemini comes to iOS 18 and Apple’s family of devices later this year, one thing is clear: Generative AI is everywhere, and soon, all of your devices will have a version of it, whether you want it or not.

To stay on the safe side, never tell an AI bot what you wouldn’t tell your mother, and even then, some words are best said strictly between the humans in your life.

What 'Dune' teaches us about human achievement and the dangers of AI



One of the superb concepts of "Dune" that didn’t make it into the movie was the Butlerian Jihad. This is not the jihad that Paul commences, but rather an event long in the past that had drastic implications for the universe of Dune. In short, the Butlerian Jihad was a war on AI and thinking machines (computers). The jihad was incited by a machine decreeing an abortion, and that was the straw that broke the camel’s back. Humanity was already on the verge of being replaced, but when machines were beginning to determine who lived and died, mankind was losing its sovereignty as well.

This crusade against thinking technology strikes at looming questions that grow bigger in our lives by the day. We outsource our energy and capabilities to a tool whenever we use technology. Typically, this is well and good. An axe is far more efficient at splitting wood than attempting to do so with one’s hands, and this frees up a person to spend his energies elsewhere.

But as technology advances, we perpetually outsource ourselves to the devices around us. When we create a car, we use a device to substitute our legs. Again, this is good, as it allows far more efficient travel. But what happens when technology is entirely substituting the human individual?

Now, I am not necessarily referring to the AGI, but what happens to vast chunks of the population when a machine can do everything they can but better? What happens when we have created tools that have abolished the need for men? We made tools to serve us, but now they have replaced us. Is that a good thing? Can technology advance too far? Can we even stop technology from advancing? Huge numbers of people can no longer effectively live without modern transportation. Can we return? Should we return?

"Dune" presents us with a theoretical world where technological progression has been halted. And while it’s far from a perfect world, I think it’s a better, wiser one than we have now. Technology is not necessarily good because it is advanced. It needs to justify itself. I think we need to adopt an attitude of skepticism, certainly given the current state of the modern world. We may be in a better material position, but with skyrocketing rates of mental illness, drug abuse, and suicide, something has clearly gone wrong somewhere.

And I don’t think it’s terrible to refrain from technology that makes your life easier at the cost of your competence. You’ll never be a great artist if you rely on inputting prompts into an AI generator, and you’ll never be a talented writer if you exclusively use ChatGPT. Those skills have to be developed and refined the hard way. Otherwise, you’re just like everyone else using AI generators and ChatGPT.

In “Dune,” this type of person is called a mentat. This individual is a social adaptation to the lack of computers and advanced algorithmic calculators. Much like a savant, mentats can perform almost impossibly complex computations in their heads in only a few seconds.

Screenshot from Youtube


Now, that power is probably infeasible for us, but the concept is ever-present in our lives. If you want to be physically fit, you have to actually exercise those muscles. Refraining from technology that substitutes for your muscles is one method of gaining strength. And with strength, you gain a little control as well. Now, you are not relying on devices that break down or malfunction. It’s all on you.

That principle extends to nearly every facet of life. With careful restraint, you can develop within yourself all that unrealized potential you are wasting away. The human being was not made to be at rest. Human beings were made to do work, and it is only through work that a person becomes truly remarkable.

However, the most important lesson of the Butlerian Jihad is that it presents a world where humanity has regained control of itself. We often think our lives are insignificant specks in the grand scheme. After all, what can one man do against the march of progress? If you have problems with where the world is heading, how could you fix things, especially when you are one among billions?

But "Dune" presents a more hopeful outlook. We can take back control in our lives. We can say no to our desires and appetites to build ourselves up. We can say no to the march of the world. And I think that is an inspiring thought.