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Dad wrote opaque, elliptical, experimental works of enormous profanity… The upshot was 70 years of writing on crumbling yellow onionskin, dot-matrix prints with the tractor feeds still attached, and bright white laser output, along with more than 10,000 ancient WordPerfect files and blog entries, including many repeats. Now all mine to archive.
[…]
After I parsed and processed and batched his digital legacy, it came to 7,382 files and around 7 gigabytes.
The sum of Frank took two days and nights to upload to the Internet Archive
[…]
In time, we all end up in a folder somewhere, if we’re lucky. Frank belongs to the world now; I released the files under Creative Commons 0, No Rights Reserved. And I know he would have loved his archive.
Visit Frank on the Internet Archive.
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I am surprised that, at least according to all reporting I’ve seen, Apple isn’t planning to build haptic integrations between their existing Watch product and upcoming Vision Pro headset.
It seems like such a great way to offer additional value to owners of both products.
I have no doubt Apple could create an uncanny sensory feedback experience for hand tracking using Watch haptics alone. For example, think about the haptic feedback you get when using the Digital Crown to scroll through a list on the watch. Imagine applying that to the act of turning a virtual dial in AR.
Ever since 2015, the trackpads in all of Apple’s laptops have been solid state—the “click” is simulated, there are no moving parts. They have arguably never felt better. In a sense, they are better than the genuine thing. More real.
Adding physicality to the VisionOS interface will both ground it in reality and deepen immersion while providing an instant level of familiarity to those using the new platform.
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§ I harvested our first sugar snap peas and strawberries of the season. There isn’t much, this early in the season, but eating something you’ve grown yourself is always a great feeling.
§ While sawing down tree branches a few weeks ago I set aside a couple of the larger branches, intending to use them to make a cat tree.
I finally got started building it this week!
I chose one of the branches, stripped off all of its bark, and wrapped the base in a thick green jute. The cats have already taken some interest in it.
Unfortunately, the whole thing is attached to a 16” round base plate that is, I’ve come to find out, nowhere near sturdy enough. It looks like I’ll need to learn how to pour concrete to make it new base for it all.
§ I saw two movies, Blackberry and Tetris, which feels like two different takes on the same general premise: ”Follow a scrappy upstart technology company as they risk everything to bring their vision to life.”
There was something endearingly quirky about Tetris that I found really fun. Instead of using chapters, the film was broken out into “levels” with funky pixel art animations preceding each one. In comparison, Blackberry was conventional—a modest retelling of an interesting story rather than an interesting retelling of a modest story.
§ …Speaking of blackberries
The blackberry bush I planted last year is doing amazingly well. I never expected it to come back this spring with such a vengeance. It is already at least eight feet tall and is covered in dozens of tiny white blossoms.
It is doing so well, in fact, that I decided to buy another raspberry bush after loosing two of them to a mysterious disease last summer. Fingers crossed it fairs better this year.
§ I would love to play an alternative “roguelike” version of The Depths in Tears of the Kingdom.
§ Links
- I mentioned iOS 17’s new on-device 3D scanning capabilities last week. Simon Støvring just published a new app for testing this out. Give it a download if you have the iOS beta installed.
- Using ”hackits” to teach computer science
- On canalization, an interesting thought technology
§ Recipes
- Gluten free pierogis
- Amazing. One of the easiest gluten free doughs to work with.
- Sauteed morel mushrooms
- Ever since unexpectedly getting way into mushrooms this spring, I have been looking forward to trying morels for the first time. Well, I was so excited when I finally found a bag of freshly picked morels at my usual grocery store. After finally getting the opportunity to try them it was, overall, a rather upsetting experience. Take a look at the third paragraph under the “cleaning morels” heading above if you are curious to know why—gross!
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I was excited when StabilityAI—the company behind Stable Diffusion—launched StableLM, their open source language model with a commercially permissive license. I was convinced it would become the new hub for open source community development.
Prior to the announcement, developers had coalesced around Meta’s LLaMA model which had always been a somewhat tenuous situation. It was initially only available to select researchers before it was leaked to the public. Since then, the company hasn’t been entirely clear in its messaging. On one hand, Mark Zuckerberg has expressed a desire to commodify generative AI through open source contributions. On the other hand, they have been issuing DMCA takedown requests for seemingly innocuous projects that incorporate LLaMA.
Now, two months after StableLM’s launch, it has become clear how difficult it is to redirect inertia. The open source community has continued contributing to LLaMA and development on StableLM has stalled. As I write this, there have been no updates to the StableLM code since April.
Well, it seems like Meta might be on the verge of announcing a successor to LLaMA with a more permissive license, allowing for commercial use.
Sylvia Varnham O’Regan, Jon Victor, and Amir Efrati, The Information:
Meta is working on ways to make the next version of its open-source large-language model—technology that can power chatbots like ChatGPT—available for commercial use, said a person with direct knowledge of the situation and a person who was briefed about it. The move could prompt a feeding frenzy among AI developers eager for alternatives to proprietary software sold by rivals Google and OpenAI.
Although Meta didn’t originally indend for the open source language model community to form around their models, they may as well come out and fully embrace it. It is their best chance at disrupting Microsoft and Google dominance.
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Watching language model tooling slowly mature, it is interesting to see a progressive constraining of capabilities.
Historically, programming languages have become more abstract (”higher-lever”) over time:
Assembly → C → PythonWith language models, we may have arrived at the highest possible level of abstraction—natural language—and now we are beginning to wrap back around the other way.
A high level of abstraction is great in that it lowers the barrier to entry for programming but it comes with the cost of increased ambiguity. Sure, your compiler can now try to guess your intentions but that doesn’t mean you would always like it to do that.
Even more important is the fact that language models are non-deterministic. That is, each successive time you run your “program” you might receive a different output.
This is a huge problem, almost a non-starter when it comes to integrating LLMs into traditional programming pipelines. That is why so much research has gone into making LLMs reliably output a more constrained set of tokens that can be validated according to a predetermined schema.
JSONformer, GPT-JSON, and Guidance are all examples of prior work along these lines.
Well, earlier this week OpenAI announced a new API endpoint that points to models they finetuned for exactly this purpose.
Developers can now describe functions to gpt-4-0613 and gpt-3.5-turbo-0613, and have the model intelligently choose to output a JSON object containing arguments to call those functions. This is a new way to more reliably connect GPT’s capabilities with external tools and APIs.
I can’t wait to see what people are able to accomplish using these new capabilities.
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Byron Tau and Dustin Volz, The Wall Street Journal, The Wall Street Journal:
The vast amount of Americans’ personal data available for sale has provided a rich stream of intelligence for the U.S. government but created significant threats to privacy, according to a newly released report by the U.S.’s top spy agency.
Commercially available information, or CAI, has grown in such scale that it has begun to replicate the results of intrusive surveillance techniques once used on a more targeted and limited basis, the report found.
Intelligence agencies don’t need to request a warrant for a piece of information if they can purchase it from public sources instead.
The proliferation of data brokers who specialize in compiling and selling sensitive information has only exacerbated this problem.
Quoted directly from the report:
Under the U.S. Constitution… CAl is generally less strictly regulated than other forms of information acquired by the [intelligence community (IC)], principally because it is publicly available. In our view, however, changes in CAl have considerably undermined the historical policy rationale for treating [publicly available information (PAI)] categorically as non-sensitive information, that the IC can use without significantly affecting the privacy and civil liberties of U.S. persons. For example, under Carpenter v. United States, acquisition of persistent location information… concerning one person by law enforcement from communications providers is a Fourth Amendment “search” that generally requires probable cause. However, the same type of information on millions of Americans is openly for sale to the general public. As such, IC policies treat the information as PAl and IC elements can purchase it.
I understand that it would be foolish to expect intelligence agencies to abide by a stricter set of data privacy rules than civilians. Still, I don’t feel great about public money being used to support and encourage data brokers.
In the end, you can’t sell what you don’t have. This report reinforces my view that end-to-end encryption should be the only acceptable solution for storing personal information.
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In recent years, large language models have greatly improved in their ability to perform complex multi-step reasoning. However, even state-of-the-art models still produce logical mistakes, often called hallucinations.
[…]
We can train reward models to detect hallucinations using either outcome supervision, which provides feedback based on a final result, or process supervision, which provides feedback for each individual step in a chain-of-thought… We find that process supervision leads to significantly better performance, even when judged by outcomes.
This technique was evaluated using questions from a large mathematics dataset. This is an important caveat as math is a domain that is well-versed in the practice of “showing your work.” Presumably GPT-4’s training corpus includes many instances of people walking through math problems step-by-step. The relative preformance of process supervision when it comes to questions from other domains is still unknown.
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Facebook has released another open source model as they work to commodify generative AI.
We introduce MusicGen, a single Language Model (LM) that operates over several streams of compressed discrete music representation… we demonstrate how MusicGen can generate high-quality samples, while being conditioned on textual description or melodic features, allowing better controls over the generated output.
I was amazed by Google’s MusicLM model earlier this year. Facebook provides side-by-side comparisons here that demonstrate MusicGen is clearly superior. It isn’t an enormous leap, but audio generated using Google’s model has a distinct “compressed” quality that is greatly diminished in Facebook’s implementation.
More importantly, MusicGen is completely open. Google only recently allowed beta testing of MusicLM through their AI Test Kitchen App and, even so, generations are limited to 20 seconds. Here, Facebook released both their code and model weights on GitHub and spun up a Colab notebook demo.
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§ I can see fruit beginning to develop on our blackberry, strawberry, and snap pea plants. I can’t wait for the rest of the garden to fill out—I planted two more tomato seedlings and six different types of peppers.
We also picked an almost burdensome amount of lettuce. Just as I was starting to ready myself for a week of enormous salads, Caroline had the ingenious idea of using them in our long-neglected juicer. That quickly lightened our load.
§ Speaking of my inability to stick to reading one thing at a time, I started reading The New House by David Leo Rice after seeing James Reeves’ passionate recommendation.
Frustratingly, I can’t find a digital copy of the book anywhere so not only am I jumping around too much, in this case I don’t even get to use the reMarkable tablet to help.
§ I tried to savor the new season of I Think You Should Leave and still finished it in less than a week. My favorite sketch was The Driving Crooner.
Overall, I feel like this season was maybe slightly worse than the previous two. I still highly recommend watching it, though.
§ I thought this might be the first year that I would skip the iOS beta. I made it two days before installing iOS 17 on my phone. Playing around with the updated autocorrection engine has been interesting but, overall, there is really not much to see.
§ Since its introduction at WWDC last year, I haven’t seen much mention of Apple‘s RoomPlan API. Try it out if you want a taste of the technology behind the upcoming Vision Pro headset. You can watch your iPhone construct an accurately scaled 3D model of a room—in real time—with each architectural element and furniture item segmented and tagged. It is shockingly impressive.
§ Links
- Tiny awards
- Gruber’s Vision Pro experience
- iOS 17 comes with support for on-device 3D scanning
§ Recipes
We had a lot of quail eggs we needed to use so Caroline and I made a big batch of lemon curd with the yolks and angel food cake with the egg whites. The lemon curd had a bit of a grainy texture. I am not sure if that is due to the recipe or a just a consequence of not having a proper double boiler. Regardless, it tasted great, especially as a part of lemon curd ricotta pancakes.
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It is official: Cortana is dead.
We are making some changes to Windows that will impact users of the Cortana app. Starting in late 2023, we will no longer support Cortana in Windows as a standalone app.
[…]
We know that this change may affect some of the ways you work in Windows, so we want to help you transition smoothly to the new options. Instead of clicking the Cortana icon and launching the app to begin using voice, now you can use voice and satisfy your productivity needs through different tools.
They go on to pitch their new GPT-powered “Copilot” features.
Watch out Google Assistant, you’re next.
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AI generated video still lags behind AI imagery by quite a large margin. Still, some artists are forging ahead and exploring what is possible with the tools available today.
Will Douglas Heaven, MIT Technology Review:
The Frost is a 12-minute movie in which every shot is generated by an image-making AI.
[…]
To make The Frost, Waymark took a script written by Josh Rubin, an executive producer at the company who directed the film, and fed it to OpenAI’s image-making model DALL-E 2… Then they used D-ID, an AI tool that can add movement to still images, to animate these shots, making eyes blink and lips move.
Some of the characters almost look like Kara Walker’s paper cutout silhouettes, others have more detail, as if they were assembled out of various magazine clippings, none of them look alive. There is a pervasive surreal sense that everything in The Frost’s world has been reanimated. It is weird and new and fascinating. Highly recommended.
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As the dust settles on Apple’s Vision Pro headset announcement, critical reactions are mostly all about the same thing: wearing big goggles around other people is weird and no one is going to want to do it.
Ben Thompson articulated this general critique quite clearly:
I didn’t even get into one of the features Apple is touting most highly, which is the ability of the Vision Pro to take “pictures” — memories, really — of moments in time and render them in a way that feels incredibly intimate and vivid.
One of the issues is the fact that recording those memories does, for now, entail wearing the Vision Pro in the first place, which is going to be really awkward!
…it’s going to seem pretty weird when dad is wearing a headset as his daughter blows out birthday candles
This isn’t the first time we’ve had to contend with weird new technology. Matt Birchler offers the two most likely paths the Vision Pro might take:
The question is, what’s this going to be like:
- AirPods, which many people thought looked silly at first but then people got used to them.
- Camcorders, which took decades to go from kinda awkward to mainstream over decades and massive advances in the tech.
When AirPods first launched, I remember how viscerally strange I found them. Now, not only do I use AirPods religiously, I don’t even remember why I thought they were so weird in the first place. If Apple can pull that off again, we will be in for a wild next few years.
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Apple kicked off its annual WWDC conference on Monday. Here are my initial impressions after watching the keynote:
macOS, iOS, and watchOS
- There were a lot of mentions of “on-device intelligence” and “machine learning.” No one said “AI.”
- There is a new Mac Pro with Apple Silicon as well as a 15” MacBook Air. Both will be available next week.
- The iOS 17 presentation started with “big updates to the Phone app” which I would have never in a million years guessed. I will admit, the new “Live Voicemail” feature looks great though.
- The long segment dedicated to iMessage’s “new Stickers expirence” should put to rest fears that Apple would ever feel pressed for time. Indeed, the keynote was over two hours long.
- Autocorrect in iOS 17 is powered by “a transformer-based on-device language model.” It will be able to correct on a sentence level rather than individual words.
- The Journal app that was rumored is real but won’t be available at launch—it is coming “later this year”
- Interactivity is coming to widgets on all platforms. On macOS Sonoma, you will be able to add widget to the desktop.
- You will be able to set multiple simultaneous timers
- Death Stranding will be coming to Apple Silicon Macs. There was no mention of it during the later headset discussion.
- Safari gets a new Profiles feature. I’ve always loved Containers in Firefox and have missed them since switching to Safari. It seems like a logical extension of the OS-wide Focus Mode feature they introduced last year.
- WatchOS 10 is launching with a comprehensively redesigned interface. A notable exception is the “honeycomb” app launcher which appears unchanged.
- There is still no ability for third party developers to create custom watch faces. Apple is offering the consolation prize of “a new Snoopy and Woodstock watch face.”
- iPadOS got… no new pro-level features? I am kind of shocked Apple didn’t save their recent Final Cut and Logic Pro app release announcement for this event.
One more thing
- It is official: Apple announced their new XR googles and they are called “Vision Pro”
- Apple is calling this their first “spatial computing“ device which is a better descriptor than AR/VR/XR
- They really do look a lot like ski goggles
- There is a screen on the front of them that displays your eyes. It is a weird concept that was executed in a much better way than I would have ever expected. The more I think about it—and I can’t believe I’m saying this—it might be the defining innovation here. I expect to see it copied by other hardware makers soon.
- The hardware looks bulky and awkward. The software, UX, and design language, though, looks incredible.
- For input, there is eye tracking, hand gesture recognition, voice, and a virtual keyboard. Vision Pro also works with physical Magic Keyboards and game controllers.
- The headset can capture 3D photographs and videos
- It has two hours of battery life with an external battery
- Leading up to this event, a lot of people were speculating the Vision Pro would be cheaper than it’s rumored price of $3000—in reality, it will be more expensive at $3499.
- Vision Pro is clearly a first generation product. It is expensive and has a short battery life even with bulky hardware and an external battery pack. Waiting for the second generation version is unquestionably the smartest decision. It is going to be extremely temping, though. At least I’ll have some time to decide—it will be available to purchase next year.
- I can’t wait to try them
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NPR’s Planet Money podcast has just concluded a three part series where they used generative AI to write an episode for them.
In Part 1 of this series, we taught AI how to write an original Planet Money script by feeding it real research and interviews. In Part 2, we used AI to clone the voice of our former colleague Robert Smith.
Now, we’ve put everything together into a 15-minute Planet Money episode.
I didn’t find the simulated Robert Smith voice to be particularly convincing but that might be because I have so much experience listening to the real Robert Smith. I think AI generated voices are already good enough to tackle many lower stakes applications but pacing and inflection are just too important to podcasting and we are just not quite there yet.
In terms of content, I thought the episode was, at times, slightly nonsensical and bland but overall totally passable. If I wasn’t primed in advance to expect AI content, there is a chance I wouldn’t have noticed.
I don’t think I would feel particularly good about spending too much of my time listening to wholly AI generated podcasts but I think it is somewhat inevitable once the voice simulation technology improves.
It would be fascinating to see the Planet Money team revisit this experiment in a few years.
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§ School is out. Classes are now completely finished for the year.
I just have a few meetings and some loose ends to tie up this week. After that, I have set aside a couple of weeks to enjoy the summer before my new job starts up.
§ Now that Succession has concluded, I can easily say that this final season was their best. I can’t recall that being the case with any of my other favorite shows.
Fingers crossed for a Better Call Saul-style spin-off series starring Greg or Connor.
§ I have been sawing down some stray tree branches in the backyard to give the plants access to a bit more sunlight.
Using all of the extra pliable branches I have been attempting to construct a small wattle fence. The process couldn’t be more straightforward but it is still a lot of work.
§ The video game developer Hideo Kojima is rumored to be working with Apple on a game for their upcoming XR headset.
Although I don’t think of myself as a particularly avid video game player, this is actually the news that has made me the most excited about the headset so far.
A few years ago I purchased a PlayStation 4 just to play Kojima’s previous game: Death Stranding—it isn’t impossible something similar will end up happening again here.
§ Links
§ Recipes
- Jaeyook Kimchi Bokum
- While not technically related, there is a sense in which this feel like a better version of Phat Bai Horapha which I linked to a little while back.
- I’ve seen alternative recipes for this where cabbage and carrots are included. I am definitely going to try adding those next time.
- Jaeyook Kimchi Bokum
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The conversation around Apple’s upcoming Worldwide Developers Conference understandably centers around their rumored XR headset. The launch of an entirely new computing platform will undoubtedly make for an exciting event but there is an entirely different set of possibilities that I haven’t seen discussed nearly as much this year. Aside from the big stuff, WWDC always brings a slate of equally impactful, but less flashy, changes. Here is my wishlist from that second category:
- A dedicated “Passwords” app outside of Settings
- Bonus: a refresh of Keychain Access on macOS
- The new journaling app that is rumored for iOS 17 especially if it incorporates data I already have from years past
- Some love for Apple Mail—I am getting jealous of Mimestream
- Better widgets, interactive widgets, widgets on the macOS desktop
- When I pause audio, leave the Dynamic Island’s player controls accessible for longer than a fraction of a second
- Improve notifications on macOS
- Add a clipboard manager to iOS and iPadOS
- A dedicated “Passwords” app outside of Settings
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Design involves both technological engineering and psychological engineering, and psychological engineering is harder. Doors don’t often fall off their hinges, get stuck, or snap in half—all feats of technological engineering. They do often lock accidentally, set off unintended alarms, and mislead people about how to open them—all failures of psychological engineering.
[…]
Once spotted, psychological engineering problems are tricky to solve. Unlike battery life or fire resistance, “intuitiveness" is hard to quantify and thus hard to optimize. The fundamental attribution error leads us to blame design failures on stupid people rather than stupid products.
[…]
Anyone who can overcome these challenges is rewarded with indifference. Psychological engineering problems are hard to spot in the first place, so people rarely notice when you solve them. People hate pushing a pull door, but they don’t think at all when they push a push door. Unlike technological engineering, which can be explained and sold (“This car gets 55 miles to the gallon!”) and thus copied and improved, good psychological engineering melts into the background.
The good designs that don’t spread, then, are probably solving psychological engineering problems. Technological engineering marches ever forward, which is why the next phone you get will be slimmer and faster and last longer on a single charge. Psychological engineering remains stuck, which is why the next building you enter will probably be full of Norman Doors.
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We introduce Voyager, the first LLM-powered embodied lifelong learning agent in Minecraft that continuously explores the world, acquires diverse skills, and makes novel discoveries without human intervention… Voyager is able to utilize the learned skill library in a new Minecraft world to solve novel tasks from scratch
[…]
Voyager exhibits superior performance in discovering novel items, unlocking the Minecraft tech tree, traversing diverse terrains, and applying its learned skill library to unseen tasks in a newly instantiated world. Voyager serves as a starting point to develop powerful generalist agents without tuning the model parameters.
Last month we saw Sanford researchers create a version of The Sims inhabited by LLM-powered agents. These agents exhibited surprisingly complex social skills.
This new research shows that agents based on a similar architecture can create and explore in novel environments.
As this technology becomes less expensive, we will start to see incredible new virtual experiences that were previously unimaginable.
As capabilities improve further, we will reach the point where we pass some sort of fundamental threshold—like the uncanny valley—where the characters that inhabit our virtual environments become too lifelike.
At its height, people spent a lot of time playing Second Life and it, well, looked like Second Life. We don’t even need hyperrealistic experiences for things to start getting scary, though. Imagine a version of Grand Theft Auto where every NPC has their own unique set of ambitions and relationships. I wouldn’t be surprised if someone could hack that together with the technology available today. Once that happens, we will need to start having some difficult conversations.
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Ilia Blinderman, from the excellent visual journalism publication The Pudding, shares some of what he has learned about how to create well designed, data-driven essays:
We have a curious tendency of assuming that people who can do certain things that we cannot are imbued with superior innate talents… This may be especially common for the sort of code-driven interactive data visualizations which we work on, since they rely on an odd grab-bag of skills —critical thought, design, writing, and programming — that people in many other professions may have neither a full awareness of, nor full expertise in.
[…]
I’m hoping that my putting this guide together will help remove some of the unnecessary mystique surrounding data viz, and demonstrate that the only things that separate a beginner from a speaker on the conference circuit [are] time and practice.
I recently wrote about how I am currently wrapping up a big data visualization project with my students—I wish I had known about this resource earlier!
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In this paper, we introduce the Tree-of-Thought (ToT) framework, a novel approach aimed at improving the problem-solving capabilities of auto-regressive large language models (LLMs). The ToT technique is inspired by the human mind’s approach for solving complex reasoning tasks through trial and error.
Here is the problem: LLMs do not know whether the answer they are currently generating is accurate or optimal. Once they start down a particular path, they are locked in, unable to reconsider unless they are later prompted to.
Language models do not explicitly perform logical correctness checks as it generates a new token based on the previous tokens. This limits the model’s capacity to rectify its own mistakes. A minor error could be amplified as the model generates more tokens
Tree-of-thought lets the model explore multiple solutions, backtracking when a particular solution is deemed to be suboptimal. Compared to previous “chain-of-thought” prompting techniques, tree-of-thought gives the LLM more computation time before arriving at a final conclusion.
As mentioned above, LLMs typically generate a token based on the preceding sequence of tokens without backward editing. On the contrary, when a human solver attempts to solve a problem, she might backtrack to previous steps if a derivation step is incorrect, or if she becomes stuck and is unable to make further progress towards arriving at the final answer.
[…]
[The tree-of-thought framework] incorporates several components which enhance the problem solving capability of the LLM, including a prompter agent, a checker module, a memory module, and a ToT controller.
It is fascinating to think about what studying language models can teach us about our own cognition.
Related: Loom—A “multiversal tree writing interface for human-AI collaboration”
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§ This was our last full week of school. There are only two more days of classes next week and then that’s it.
This might be a good time to mention that I will be starting a new job at the end of June. It is a new position at my city’s science museum that touches on a little bit of everything: some programming work, new interactive exhibit design, even some curriculum development and teaching. I am excited!
§ I have spent this entire fourth quarter of the school year teaching my third and fourth grade students using the Circuit Playground microcontrollers.
I started simple: light up the onboard LEDs. Then I added a new tiny building bock each lesson: buttons, switches, RGB color codes, how each of the built-in sensors work…
Throughout the quarter, I had three big projects.
First: Take the knowledge you have of all of the Circuit Playground’s sensors and devise a method to detect when someone picks up the circuit board.
The students came up with so many creative solutions. Some used the accelerometer, others used the photoresistor, a few even used the capacitive touch pads that surround the board. Most students realized that using a combination of multiple sensors works best.
Everyone had lots of fun testing each other’s projects. I got to take on the role of “the mastermind Circuit Playground thief”. It was great.
The second big project was to recreate the classic arcade game Cyclone, step by step. The students loved creating their own gameplay variants.
Finally, all of this is culminated in a big end of the year project that I am especially excited about.
Each student thought of a research question—Is the lunch room louder on Mondays or Fridays? Which group gets more exercise at recess—those playing soccer or football?—then they used the Circuit Playground boards to collect relevant data. After collecting their data, they analyzed it to see whether or not their hypothesis was correct.
Overall, I have immensely enjoyed teaching with these boards.
§ One week later, I still really like the reMarkable tablet. You can really only do two things—read and draw—so it is hard to get distracted while using it. I have been reading much more than I typically would.
It is actually easier to get new articles and books on the device than I anticipated. For the most part this is great, but it doesn’t do much to encourage me to stick with reading one thing at a time. Consequently, I have been jumping around a lot, reading a bit of everything.
§ I got beta access to Google’s new generative AI search features. The UI feels a bit busy and confusing, particularly on mobile, but the overall functionality is actually better than I expected.
Unfortunately, it only works in Chrome and the Google iOS app right now. I can’t wait for it to come to Safari.
§ I am getting dangerously close to becoming a mushroom forager. I’ve got the books.
§ Links
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Last month, when the viral AI-generated “Drake” song was blowing up, the musician Grimes told fans that she would split royalties “on any successful AI generated song that uses my voice.”
I am honestly surprised by the extent that she followed through with this.
Grimes subsequently released software designed to assist in the generation of these songs—“If you go to elf.tech u can upload ur voice singing or record directly into the app… It will output the same audio but with my voice.”
She recently spoke with Joe Coscarelli at The New York Times about some of the music that has been produced so far.
People keep getting really upset, being like, “I want to hear something that a human made!” And I’m like, humans made all of this. You still have to write the song, produce the song and sing the vocal. The part that is A.I. is taking the harmonics and the timbre of the vocal and moving them to be consistent with my voice, as opposed to the person’s original voice. It’s like a new microphone.
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Sam Altman has been spending the past few weeks advocating in favor of AI regulations.
In terms of both potential upsides and downsides, superintelligence will be more powerful than other technologies humanity has had to contend with in the past. We can have a dramatically more prosperous future; but we have to manage risk to get there.
[…]
We are likely to eventually need something like an IAEA for superintelligence efforts; any effort above a certain capability (or resources like compute) threshold will need to be subject to an international authority that can inspect systems, require audits, test for compliance with safety standards, place restrictions on degrees of deployment and levels of security, etc.
To be fair, they say open source models are totally fine… as long as they don’t get too good:
We think it’s important to allow companies and open-source projects to develop models below a significant capability threshold, without the kind of regulation we describe here… the systems we are concerned about will have power beyond any technology yet created, and we should be careful not to water down the focus on them by applying similar standards to technology far below this bar.
Last week, Altman was in Washington DC discussing these topics with lawmakers.
Cat Zakrzewski, The Washington Post:
OpenAI chief executive Sam Altman delivered a sobering account of ways artificial intelligence could “cause significant harm to the world” during his first congressional testimony, expressing a willingness to work with nervous lawmakers to address the risks presented by his company’s ChatGPT and other AI tools.
Altman advocated a number of regulations — including a new government agency charged with creating standards for the field — to address mounting concerns that generative AI could distort reality and create unprecedented safety hazards.
In October, 2022 Sam Bankman Fried published a “draft of a set of standards” for the cryptocurrency industry. He had previously been spearheading the effort to lobby congress to adopt similar regulatory measures industry-wide.
Less than one month later, his exchange, FTX declared bankruptcy. He was subsequently indicted with “wire fraud, conspiracy to commit commodities fraud, conspiracy to commit securities fraud and conspiracy to commit money laundering” among other charges.
It’s actually kind of typical: when companies get big enough and fear newer upstart competition, they’re frequently quite receptive to regulations… established companies often want those regulations in order to lock themselves in as the dominant players, and to saddle the smaller companies with impossible to meet compliance costs.
OpenAI should be commended for kickstarting our current generative AI development explosion and they are still, without question, the leader in this space.
This move should be called out for what it is, though—a blatant ploy for regulatory capture.
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It is hard to deny that Google killed it during their IO conference earlier this month. They were clearly kicked into action by AI developments spearheaded by Microsoft and OpenAI and it showed.
Well, Microsoft held their annual Build conference yesterday. How did they respond?
With a whimper.
Microsoft’s close partnership with OpenAI might be their smartest move in recent memory and they are squandering it with a complete lack of any coherent product vision.
Their big announcement was Copilot for Windows—a button on the Windows 11 taskbar that opens up what appears to be a Bing AI web view. Sure, Microsoft made sure to note that Copilot will be able to “customize the settings” on your PC although I am sure you will still get thrown into control panel if you need to accomplish anything substantial.
The only other notable announcement is that “Browsing with Bing” will soon be the default ChatGPT experience and that ChatGPT plugins will soon be compatible with Bing AI.
It isn’t a secret that Bing AI and ChatGPT share the same underlying model from OpenAI. And, unlike Google’s new generative AI augmented search, Microsoft didn’t put any thought into what a meaningful user experience for an AI assisted Bing would look like.
It is just a chat window, just like ChatGPT.
I don’t understand why I should want to use Bing AI instead. I don’t think Microsoft knows why, either.
So Build was boring. Maybe Satya is just happy to have made Google dance. But Google is running now. They haven’t caught up yet but the gap is quickly closing.
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The anonymous writer behind the brr.fyi blog has been writing about their experience living and working at an Antarctic research station.
On May 12th, the sun passed below the horizon. It will be dark for the next eight months. From now until August, there will be no visitors and no resupply trips—during the long arctic winter the environment is too harsh for safe air travel. Everyone is truly isolated.
Oh, and when you decide to venture outside, everything is red:
There are a number of science projects that can only happen during the winter here, because of the unique environmental characteristics of the South Pole (darkness, elevation, weather, air quality, etc). A few of these are extremely sensitive to broad-spectrum visible light.
[…]
To protect the science experiments, we work hard to avoid any stray broad-spectrum light outside. This means all our station windows are covered, all our exterior navigation lights are tinted red, and we’re only permitted to use red headlamps and flashlights while walking outside.
Once it becomes closer to fully dark, these lights take on a surreal quality.
Make sure you check out the photos and videos the author shared. Surreal doesn’t even begin to describe it.
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