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James Webb Space Telescope Spots Mysterious, Free-Floating Mass

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The strange body could be a rogue planet or a so-called 'failed star.'

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samuel
8 days ago
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I remember reading somewhere a long time ago that the vast majority of planets in the universe are rogue planets.
Cambridge, Massachusetts
fancycwabs
7 days ago
Huh. One of the reasons Pluto's not considered a planet anymore is that it doesn't "clear its orbit." Once something no longer has an orbit, is it still considered a planet? I guess I could ask my nephew the astrophysicist.
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iPhone 16e Versus iPhone SE 3. How Much Did Apple’s ‘Budget’ iPhone Really Change?

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The iPhone 16e seems sure to go down in tech history as a pocket-sized example of feature creep, in which a development team keeps adding more and more fancy tech to the point they undermine the product’s value.

It packs a better chip and better screen than we were expecting, but what’s the point? The iPhone SE 3, officially known as the iPhone SE (3rd Generation), came out on March 18, 2022 as a mid-priced phone that also served the Apple-faithful and Apple-curious who bemoaned that iPhone screens were growing too large to comfortably use.

Then we got our official glimpse of the newest iPhone when Apple announced it on Wednesday, February 19. The first major surprise was that the SE moniker was dead. Apple’s new tiny, budget iPhone would henceforth be known as the iPhone 16e, and it wasn’t very tiny at all. And come to think of it, it wasn’t very budget, either.

a lot more expensive

The iPhone SE 3’s retail price started at $430, and a major selling point of the iPhone SE was that you could have Apple’s it-just-works slickness and intuitive iOS ecosystem for… not cheap, but cheaper than the high price of entry that even base-level iPhones require.

I thought (what we now know is called) the iPhone 16e would target the $400-500 price bracket that all three previous generations of the iPhone SE occupied, and boy, was I wrong. The iPhone 16e jacks up the entry-level price to $599. It’s no longer a budget smartphone.

look at all that screen — credit: apple

It is a higher-spec phone than the mid-budget iPhone SE family ever was, but is it needed? An iPhone 16 is only $200 more. Once you’re that close in cost, you may as well spring for the iPhone 16.

For that extra $200, you gain dual camera lenses (it adds a 12 megapixel ultra-wide), macro photography, sweet Dynamic Island, faster MagSafe wireless charging, cinematic video mode, faster Wi-Fi 7 (versus the iPhone 16e’s Wi-Fi 6), and spatial photos.

so long, smaller-screen iphone

Aside from price, the iPhone SE’s other major calling card was its smaller screen size. As smartphones get bigger and bigger, people with hands on the small side are left behind juggling a handheld device that doesn’t quite fit in their hand, at least not comfortably or ergonomically.

The iPhone SE 3’s screen measures 4.7 inches, and the case’s overall dimensions measure 5.45 by 2.65 inches, with a thickness of 0.29 inch. Next to the iPhone 16e’s 5.78 by 2.82 inches, and a thickness of 0.31 inch, it’s functionally identical. Not only that, but the iPhone 16e packs a much larger screen, at 6.1 inches.

All good, right? More screen for roughly the same overall size. But it’s not only the overall size of the device that frustrates folks with smaller hands. It’s also the reach across the screen to type and swipe their way through apps, and so that far larger screen on the iPhone 16e presents the same, familiar size problem as the standard iPhone 16 and iPhone 16 Pro do. Once again, there’s no iPhone option for people who value a smaller screen.

How do you like them Apples? Myself, I’m still trying to decide. The SE made a clear case for itself in the Apple lineup. It was quite different from the main lineup of iPhones and significantly cheaper. The iPhone 16e is neither.

It’s not budget enough to be a true successor to the SE, and it intrudes on the iPhone 16’s turf. The strongest case against the iPhone 16e is the iPhone 16 itself.

The post iPhone 16e Versus iPhone SE 3. How Much Did Apple’s ‘Budget’ iPhone Really Change? appeared first on VICE.

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samuel
15 days ago
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I don't know what I'm going to do with my iPhone SE 3 (my second SE, too, coming from the iPhone 7) but I'm going to avoid upgrading to a larger screen for as long as I can.
Cambridge, Massachusetts
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Three Observations - Sam Altman

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Our mission is to ensure that AGI (Artificial General Intelligence) benefits all of humanity. 

Systems that start to point to AGI* are coming into view, and so we think it’s important to understand the moment we are in. AGI is a weakly defined term, but generally speaking we mean it to be a system that can tackle increasingly complex problems, at human level, in many fields.

People are tool-builders with an inherent drive to understand and create, which leads to the world getting better for all of us. Each new generation builds upon the discoveries of the generations before to create even more capable tools—electricity, the transistor, the computer, the internet, and soon AGI.

Over time, in fits and starts, the steady march of human innovation has brought previously unimaginable levels of prosperity and improvements to almost every aspect of people’s lives.

In some sense, AGI is just another tool in this ever-taller scaffolding of human progress we are building together. In another sense, it is the beginning of something for which it’s hard not to say “this time it’s different”; the economic growth in front of us looks astonishing, and we can now imagine a world where we cure all diseases, have much more time to enjoy with our families, and can fully realize our creative potential.

In a decade, perhaps everyone on earth will be capable of accomplishing more than the most impactful person can today.

We continue to see rapid progress with AI development. Here are three observations about the economics of AI:

1. The intelligence of an AI model roughly equals the log of the resources used to train and run it. These resources are chiefly training compute, data, and inference compute. It appears that you can spend arbitrary amounts of money and get continuous and predictable gains; the scaling laws that predict this are accurate over many orders of magnitude.

2. The cost to use a given level of AI falls about 10x every 12 months, and lower prices lead to much more use. You can see this in the token cost from GPT-4 in early 2023 to GPT-4o in mid-2024, where the price per token dropped about 150x in that time period. Moore’s law changed the world at 2x every 18 months; this is unbelievably stronger. 

3. The socioeconomic value of linearly increasing intelligence is super-exponential in nature. A consequence of this is that we see no reason for exponentially increasing investment to stop in the near future.

If these three observations continue to hold true, the impacts on society will be significant.

We are now starting to roll out AI agents, which will eventually feel like virtual co-workers.

Let’s imagine the case of a software engineering agent, which is an agent that we expect to be particularly important. Imagine that this agent will eventually be capable of doing most things a software engineer at a top company with a few years of experience could do, for tasks up to a couple of days long. It will not have the biggest new ideas, it will require lots of human supervision and direction, and it will be great at some things but surprisingly bad at others.

Still, imagine it as a real-but-relatively-junior virtual coworker. Now imagine 1,000 of them. Or 1 million of them. Now imagine such agents in every field of knowledge work.

In some ways, AI may turn out to be like the transistor economically—a big scientific discovery that scales well and that seeps into almost every corner of the economy. We don’t think much about transistors, or transistor companies, and the gains are very widely distributed. But we do expect our computers, TVs, cars, toys, and more to perform miracles.

The world will not change all at once; it never does. Life will go on mostly the same in the short run, and people in 2025 will mostly spend their time in the same way they did in 2024. We will still fall in love, create families, get in fights online, hike in nature, etc.

But the future will be coming at us in a way that is impossible to ignore, and the long-term changes to our society and economy will be huge. We will find new things to do, new ways to be useful to each other, and new ways to compete, but they may not look very much like the jobs of today. 

Agency, willfulness, and determination will likely be extremely valuable. Correctly deciding what to do and figuring out how to navigate an ever-changing world will have huge value; resilience and adaptability will be helpful skills to cultivate. AGI will be the biggest lever ever on human willfulness, and enable individual people to have more impact than ever before, not less.

We expect the impact of AGI to be uneven. Although some industries will change very little, scientific progress will likely be much faster than it is today; this impact of AGI may surpass everything else.

The price of many goods will eventually fall dramatically (right now, the cost of intelligence and the cost of energy constrain a lot of things), and the price of luxury goods and a few inherently limited resources like land may rise even more dramatically.

Technically speaking, the road in front of us looks fairly clear. But public policy and collective opinion on how we should integrate AGI into society matter a lot; one of our reasons for launching products early and often is to give society and the technology time to co-evolve.

AI will seep into all areas of the economy and society; we will expect everything to be smart. Many of us expect to need to give people more control over the technology than we have historically, including open-sourcing more, and accept that there is a balance between safety and individual empowerment that will require trade-offs.

While we never want to be reckless and there will likely be some major decisions and limitations related to AGI safety that will be unpopular, directionally, as we get closer to achieving AGI, we believe that trending more towards individual empowerment is important; the other likely path we can see is AI being used by authoritarian governments to control their population through mass surveillance and loss of autonomy.

Ensuring that the benefits of AGI are broadly distributed is critical. The historical impact of technological progress suggests that most of the metrics we care about (health outcomes, economic prosperity, etc.) get better on average and over the long-term, but increasing equality does not seem technologically determined and getting this right may require new ideas.

In particular, it does seem like the balance of power between capital and labor could easily get messed up, and this may require early intervention. We are open to strange-sounding ideas like giving some “compute budget” to enable everyone on Earth to use a lot of AI, but we can also see a lot of ways where just relentlessly driving the cost of intelligence as low as possible has the desired effect.

Anyone in 2035 should be able to marshall the intellectual capacity equivalent to everyone in 2025; everyone should have access to unlimited genius to direct however they can imagine. There is a great deal of talent right now without the resources to fully express itself, and if we change that, the resulting creative output of the world will lead to tremendous benefits for us all.


Thanks especially to Josh Achiam, Boaz Barak and Aleksander Madry for reviewing drafts of this.

*By using the term AGI here, we aim to communicate clearly, and we do not intend to alter or interpret the definitions and processes that define our relationship with Microsoft. We fully expect to be partnered with Microsoft for the long term. This footnote seems silly, but on the other hand we know some journalists will try to get clicks by writing something silly so here we are pre-empting the silliness…

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samuel
31 days ago
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Agency is what we need to be teaching kids
Cambridge, Massachusetts
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1 public comment
gedcarroll
30 days ago
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some interesting takes regardless of how you feel about the direction that Salm Altman is taking things
Hong Kong and London

AI-generated tools can make programming more fun

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I want to tell you about a neat experience I had with AI-assisted programming this week. What’s unusual here is: the AI didn’t write a single line of my code. Instead, I used AI to build a custom debugger UI… which made it more fun for me to do the coding myself.

* * *

I was hacking on a Prolog interpreter as a learning project. Prolog is a logic language where the user defines facts and rules, and then the system helps answer queries. A basic interpreter for this language turns out to be an elegant little program with surprising power—a perfect project for a fun learning experience.

The trouble is: it’s also a bit finicky to get the details right. I encountered some bugs in my implementation of a key step called unification—solving symbolic equations�—which was leading to weird behavior downstream. I tried logging some information at each step of execution, but I was still parsing through screens of text output looking for patterns.

I needed better visibility. So, I asked Claude Artifacts to whip up a custom UI for viewing one of my execution traces. After a few iterations, here’s where it ended up:

I could step through an execution and see a clear visualization of my interpreter’s stack: how it has broken down goals to solve; which rule it’s currently evaluating; variable assignments active in the current context; when it’s come across a solution. The timeline shows an overview of the execution, letting me manually jump to any point to inspect the state. I could even leave a note annotating that point of the trace.

Oh yeah, and don’t forget the most important feature: the retro design 😎.

Using this interactive debug UI gave me far clearer visibility than a terminal of print statements. I caught a couple bugs immediately just by being able to see variable assignments more clearly. A repeating pattern of solutions in the timeline view led me to discover an infinite loop bug.

And, above all: I started having more fun! When I got stuck on bugs, it felt like I was getting stuck in interesting, essential ways, not on dumb mistakes. I was able to get an intuitive grasp of my interpreter’s operation, and then hone in on problems. As a bonus, the visual aesthetic made debugging feel more like a puzzle game than a depressing slog.

* * *

Two things that stick out to me about this experience are 1) how fast it was to get started, and 2) how fast it was to iterate.

When I first had the idea, I just copy-pasted my interpreter code and a sample execution trace into Claude, and asked it to build a React web UI with the rough functionality I wanted. I also specified “a fun hacker vibe, like the matrix”, because why not? About a minute later (after a single iteration for a UI bug which Claude fixed on its own), I had a solid first version up and running:

My prompt to Claude

That fast turnaround is absolutely critical, because it meant I didn’t need to break focus from the main task at hand. I was trying to write a Prolog interpreter here, not build a debug UI. Without AI support, I would have just muddled through with my existing tools, lacking the time or focus to build a debug UI. Simon Willison says: “AI-enhanced development makes me more ambitious with my projects”. In this case: AI-enhanced development made me more ambitious with my dev tools.

By the way: I was confident Claude 3.5-Sonnet would do well at this task, because it’s great at building straightforward web UIs. That’s all this debugger is, at the end of the day: a simple view of a JSON blob; an easy task for a competent web developer. In some sense, you can think of this workflow as a technique for turning that narrow, limited programming capability—rapidly and automatically building straightforward UIs—into an accelerant for more advanced kinds of programming.

Whether you’re an AI-programming skeptic or an enthusiast, the reality is that many programming tasks are beyond the reach of today’s models. But many decent dev tools are actually quite easy for AI to build, and can help the rest of the programming go smoother. In general, these days any time I’m spending more than a minute staring at a JSON blob, I consider whether it’s worth building a custom UI for it.

* * *

As I used the tool in my debugging, I would notice small things I wanted to visualize differently: improving the syntax display for the program, allocating screen real estate better, adding the timeline view to get a sense of the full history.

Each time, I would just switch windows, spend a few seconds asking Claude to make the change, and then switch back to my code editor and resume working. When I came back at my next breaking point, I’d have a new debugger waiting for me. Usually things would just work the first time. Sometimes a minor bug fix was necessary, but I let Claude handle it every time. I still haven’t looked at the UI code.

Eventually we landed on a fairly nice design, where each feature had been motivated by an immediate need that I had felt during use:

Claude wasn’t perfect—it did get stuck one time when I asked it to add a flamegraph view of the stack trace changing over time. Perhaps I could have prodded it into building this better, or even resorted to building it myself. But instead I just decided to abandon that idea and carry on. AI development works well when your requirements are flexible and you’re OK changing course to work within the current limits of the model.

Overall, it felt incredible that it only took seconds to go from noticing something I wanted in my debugger to having it there in the UI. The AI support let me stay in flow the whole time; I was free to think about interpreter code and not debug tool code. I had a yak-shaving intern at my disposal.

This is the dream of malleable software: editing software at the speed of thought. Starting with just the minimal thing we need for our particular use case, adding things immediately as we come across new requirements. Ending up with a tool that’s molded to our needs like a leather shoe, not some complicated generic thing designed for a million users.

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samuel
78 days ago
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I find myself doing this too. Building custom tools just for inspecting data for a one-off. Claude's UI is great, but Cursor is where I go for the actual implementation.
Cambridge, Massachusetts
sredfern
29 days ago
Have you tried roo-code as a vscode extension?
samuel
28 days ago
Just installed it in Cursor. I've been using Composer. Why use roo-code over composer?
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Trying out QvQ - Qwen's new visual reasoning model

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I thought we were done for major model releases in 2024, but apparently not: Alibaba's Qwen team just dropped the Apache2 2 licensed QvQ-72B-Preview, "an experimental research model focusing on enhancing visual reasoning capabilities".

Their blog post is titled QvQ: To See the World with Wisdom - similar flowery language to their QwQ announcement QwQ: Reflect Deeply on the Boundaries of the Unknown a few weeks ago in November.

It's a vision-focused follow-up to QwQ, which I wrote about previousy. QwQ is an impressive openly licensed inference-scaling model: give it a prompt and it will think out loud over many tokens while trying to derive a good answer, similar to OpenAI's o1 and o3 models.

The new QvQ adds vision to the mix. You can try it out on Hugging Face Spaces - it accepts an image and a single prompt and then streams out a very long response where it thinks through the problem you have posed it. There's no option to send a follow-up prompt.

I've tried it out with a bunch of things, with mixed results - but it's really fun seeing how it works through a problem.

My most successful prompt was "Count the pelicans" with this image:

A photograph of four glorious young California Brown Pelicans perched on a dock. The back end of another pelican is visible at the front of the photo.

Here's the full response. Some highlights:

So I've got this picture of some pelicans, and I need to count them. Let me see... First off, I know that pelicans are those big birds with the massive beaks, right? [...]

Let me try counting again, more carefully this time. Starting from the left:

  1. The first pelican is fully visible, standing at the front.
  2. Behind it, slightly to the right, is the second pelican.
  3. Then, further back, there's a third pelican.
  4. And next to that one, there's a fourth pelican.

So, that's four pelicans in total. But, I notice that on the far right of the image, there's part of another bird, maybe a pelican's back or tail feathers, but it's not fully in the frame, so I don't think I should count it as a whole pelican.

Something about the tone of voice it uses, "First off, I know that pelicans are those big birds with the massive beaks, right?", tickles me.

I also tried this on a much harder image - it counted 17 which looks about right to me but honestly I have trouble with that image myself.

I fed in one of the ARC-AGI puzzles that o3 had failed at.

A puzzle with colored squares, where drawing a line between the single blue squares and turning any intersected rectangles blue is clearly the solution.

It produced a very lengthy chain of thought that was almost entirely incorrect, but had some interesting "ideas" in it:

[...] Let me try to think in terms of cellular automata rules, like Conway's Game of Life.

In Game of Life, each cell's state in the next generation is determined by its current state and the states of its eight neighbors.

Perhaps a similar rule applies here.

Finally, I asked it to "Estimate the height of the dinosaur" against this image (which, as it correctly noted, is actually an inflatable dragon):

A large inflatable Christmas decoration of a reindeer riding a dragon - both reindeer and dragon are wearing Christmas hats

I'm not sure this task is even possible given the lack of items in the frame of comparable known height. It had a good go at it though! I particularly enjoyed how it began:

So I've got this inflatable Christmas decoration, and it's a dragon! But not just any dragon—it's a green dragon wearing a Santa hat and a red and white scarf. And get this, there's a reindeer on its back, also wearing a Santa hat and holding onto the dragon's wings. It's pretty festive and colorful, with lots of vibrant greens, reds, and yellows.

The dragon has these big, friendly eyes and a smiling face, which makes it look really cheerful. Its wings are spread out, and it has white claws on its feet. The reindeer is brown with antlers and seems to be enjoying the ride on the dragon's back.

Now, the question is, how tall is this inflatable dragon? I need to estimate its height. Let me see. I'm standing next to it, and I'm about 5 feet 10 inches tall. The dragon is definitely taller than me. Maybe around 8 or 9 feet high? But I should try to be more precise.

I wonder how it decided that its own height was 5 feet 10 inches!

Running QwQ locally

All of my experiments so far have used the hosted Hugging Face demo. I'm hoping to try it out on my own laptop soon - I think it should just fit in 64GB of M2, maybe with a smaller quantization.

Right now the options are:

As a happy user of Ollama's qwq port I'm hoping they add a QwQ release at some point soon as well.

Tags: ai, generative-ai, llms, hugging-face, vision-llms, qwen, inference-scaling

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samuel
79 days ago
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I wonder how large of an M4 Pro or M4 Max I’ll need to run this model locally. Visual reasoning locally means I can throw some interesting problems at it and run it all night. Find needles in a haystack of my own photo library, for instance.
Cambridge, Massachusetts
kglitchy
78 days ago
That's a great idea! What are some use cases for information you would want to gather?
samuel
78 days ago
I want to classify photos so I can more easily make year-end photo books
samuel
78 days ago
Also, I'm about to launch embeddings (for text) on NewsBlur (try it out at staging.newsblur.com - click on the Related buttons in feed titles and at the bottom of stories) and this sort of transformer based classifier would be hugely helpful
kglitchy
77 days ago
Great ideas and I like the related stories idea!
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D Combinatorics

1 Comment and 2 Shares
Look, you can't complain about this after giving us so many scenarios involving N locked chests and M unlabeled keys.
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samuel
105 days ago
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Lol
Cambridge, Massachusetts
agwego
104 days ago
C&O Nerds
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