Tag: data

Magic and Mayhem (Predictions 2026, #3)

Magic maker

Do you remember the last time you felt the magic? When you encountered something truly novel, something that was both surprising and at the same time deeply familiar, because you had imagined such a thing, but until that very moment, believed it impossible?

I’ve had only a handful of such moments in my long relationship with digital technology. The first was in 1981, when I programmed a game of tic-tac-toe on an underpowered IBM PC. I compiled the crude lines of code I’d been assigned to write, issued the command “RUN” at the C: prompt, and damned if the thing didn’t actually work.

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CloudFlare To The AI Industry: Pay Up!

Cloudflare founders Matthew Prince and Michelle Zatlyn from a 2015 SXSW presentation (image)

There are precious few companies in the tech world that are willing to stick their necks out and “do the right thing,” and even fewer who both operate at Internet scale and enjoy Wall Street’s unabashed fandom.

In fact, I can only think of one: Cloudflare. And today, the $65 billion public company* announced a new policy that has the potential to tilt the balance of the Internet back toward the little guys. Starting this morning, Cloudflare will automatically block AI crawlers from copying the content of every website the company protects. And it’s doing it for free.

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AI Is Breaking The Internet. Can Bill Gross Fix It?

Bill Gross, ocean boiler.

Bill Gross has been here before. 

Back when the Internet was young, when the dot-com wave broke across the monied shoals of Wall Street opportunism, Gross built a world-changing company, took it public, then sold it for billions. 

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Is AI the “Big Bang” or Merely a “Turning Point”? Much Depends on the Answer

According to scholar Carlota Perez, one of tech’s most revered theorists, society regularly goes through technology-driven “revolutions.” These structural cycles can take fifty years or more, and are defined by core technologies which shape life as we know it. Her list of previous cycles include the Industrial Revolution; The Age of Steam and Railways; The Age of Steel, Electricity and Heavy Engineering; and The Age of Oil, the Automobile, and Mass Production.*

Back in the early 2000s, Perez has identified the Internet (more formally, ICT, or “information communications technologies”) as the dominant technological force driving our current age. Perez’s framing has been a favorite of pundits ever since – and has played a central role in the debate as to whether a much-hyped “Next Big Thing” – crypto, the metaverse, quantum computing – is merely a feature of an ongoing revolution, or the starting gun to an entirely new age.

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Who Owns Your AI Identity? (Hint: Not You)

As generative AI reaches a fever pitch of investment, product releases, and hype, most of us have ignored a profound flaw as we march relentlessly toward The Next Big Thing. Our most dominant AI products and services (those from OpenAI, Google, and Microsoft, for example) are deployed in the cloud via a “client-server” architecture – “a computing model where resources, such as applications, data, and services, are provided by a central server, and clients request access to these resources from the server.”

Now, what’s wrong with that? Technically, nothing.  A client-server approach isn’t controversial; in fact, it’s an efficient and productive approach for a company offering data-processing products and services.  The client – that’s be you and your device – provides input (a prompt, for example) which is relayed to the server. The server takes that input, processes it, and delivers an output back to the client.

Non-controversial, right? Well, sure, if the “server” in question is a neutral platform that’s only in the business of processing your data so you can use the services it offers. Banks, for example, use neutral client-server architectures to provide online financial services, as do most health care providers. The data you share with them isn’t used for anything other than the provision of services.

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Bluesky, Twitter, and “The Open Network”

Emily Liu at Bluesky has a timely post that I’d like to respond to. (Back in the day, when blogging was a thing, we did a lot of this – someone would write a thoughtful piece, then many others would write responses. These organic, mostly high-quality “backlinks” formed the backbone of Google’s early web dominance, but I digress, somewhat, because it’s all related).

In any case, Liu’s piece, entitled “Benefits of an Open Network,” uses a series of simple metaphors to explain how Bluesky is different from other social networks. Most readers already know this, but just in case, here’s the core of it: Bluesky is an app built on an open protocol, which means Bluesky users can engage with any other app which conforms to that protocol. In other words, Bluesky lives in an open network, albeit a rather limited one at the moment. Here’s Liu:

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Consume First, Deal with the Shit Later

https://dailymontanan.com/2021/06/12/big-bad-forest-clear-cutting-continues/

Websites are Blocking the Wrong AI Scrapers (Because AI Companies Keep Making New Ones) – 404 Media

***

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Ads, Ads Everywhere

The Times’s piece decries all the ads on TV. But is this a surprise?!

The advertising world is uncomplicated at its core, and utterly bewildering when seen from the outside. The easy bit stems from a simple axiom: Wherever you can find the attention of potential customers, you pay to get your message in front of them. That’s the essence of advertising: paying for attention. It gets complicated by the details – the medium, the message, the targeting, the tech – but wherever customers gather, advertising will follow. There’s simply too much money to be made for it to be otherwise.

So it was utterly unsurprising to learn, a few hours ago as I write this, that there will soon be ads on PayPal, driven by the data the company collects. PayPal recorded 6.5 billion payments in the first quarter of 2024 alone, according to the Journal. The company plans on creating what’s known as a “retail media network” allowing advertisers to leverage PayPal’s data to target users both on platform and off.

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Predictions 2024: It’s All About The Data

Let’s talk 2024.

2023 was a down year on the predictions front, but at least I’ve learned to sidestep distractions like Trump, crypto, and Musk. If I can avoid talking about the joys of the upcoming election and/or the politics of Silicon Valley billionaires,  I’m optimistic I’ll return to form. As always, I am going to write this post with no prep and in one stream-of-conscious sitting. Let’s get to it.

  1. The AI party takes a pause. The technology industry – and by this point, the entire capitalist experiment – is addicted to boom and bust cycles and riddled with blinkered optimism. In 2023 we allowed ourselves to dream of AI genies; we imagined trillions in future economic gains, we invested as if those gains were a certainty. In 2024, we’ll wake up and realize – as we did with the web in the early 2000s – that there’s a lot of hard work to do before our dreams become a reality. I’m not predicting an AI crash – but rather a period of digestion, with a possible side of Tums. Corporations will find their initial pilots less impactful than they hoped, and when told of the sums they must spend to course correct, insist on cutting back. Consumers will become accustomed to genAI’s outputs and begin to rethink their $20 a month subscriptions. Growth will slow, though it will not stagnate. Regulators around the world will take the year to move past Terminator nightmares and into the hard work of deeply understanding AI’s societal impact. IP holders – artists, newspapers, craftspeople – will press their lawsuits and infuse the market with uncertainty and hesitancy. In short, society will take a pause that refreshes. And that will be a good thing.
  2. But Progress Continues… It may feel like a pause, but below the tech media scorekeeping narrative, a growing ecosystem of AI startups will make important strides in areas that will matter beyond 2024. AI is driven by data, and as a society we’re not particularly good at structuring, governing, or sharing data. It makes sense that big companies with access to unholy amounts of structured data pioneered the AI era. (Of course, if you’re not a big company, and you want access to massive amounts of data, it helps to just take it without asking permission). But the AI-driven startups that will make waves in 2024 will do so by structuring discrete chunks of valuable information on behalf of very specific customers. It won’t make many headlines, but taken collectively, it’s this kind of work that will lay the groundwork for AI becoming truly magical. Read More
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On AI: What Should We Regulate?

EU classification of AI risk.

I’ve been following the story of generative AI a bit too obsessively over the past nine months, and while the story’s cooled a bit, I don’t think it any less important. If you’re like me, you’ll want to check out MIT Tech Review’s interview with Mustafa Suleyman, founder and CEO of Inflection AI (makers of the Pi chatbot). (Suleyman previously co-founded DeepMind, which Google purchased for life-changing money back in 2014.)

Inflection is among a platoon of companies chasing the consumer AI pot of gold known as conversational agents – services like ChatGPT, Google’s Bard, Microsoft’s BingChat, Anthropic’s Claude, and so on. Tens of billions have been poured into these upstarts in the past 18 months, and while it’s been less than a year into since ChatGPT launched, the mania over genAI’s potential impact has yet to abate. The conversation seems to have moved from “this is going to change everything” to “how should we regulate it” in record time, but what I’ve found frustrating is how little attention has been paid to the fundamental, if perhaps a bit less exciting, question of what form these generative AI agents might take in our lives. Who will they work for, their corporate owners, or …us? Who controls the data they interact with – the consumer, or, as has been the case over the past 20 years – the corporate entity?

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