Archive of posts with tag 'AI'

Conversational Interfaces

May 12, 2025 • #

Julian Lehr wrote an interesting post recently on the problems with conversational interfaces, with the fitting title “The case against conversational interfaces”. Here’s Julian:

We keep telling ourselves that previous voice interfaces like Alexa or Siri didn’t succeed because the underlying AI wasn’t smart enough, but that’s only half of the story. The core problem was never the quality of the output function, but the inconvenience of the input function: A natural language prompt like “Hey Google, what’s the weather in San Francisco today?” just takes 10x longer than simply tapping the weather app on your homescreen.

Voice works so well in human-to-human communication because it’s enormously flexible on both ends — for speaker and listener. Through speech we can both communicate and understand just about any idea using the same framework of 26 letters and a couple thousand words.

The speaker can walk up to anyone fluent in the language and fairly effectively communicate just about anything — commands, requests, thoughts, ideas, emotions — and have the listener comprehend.

But conversation is slow. The “bitrate” for conversational speech is peanuts compared to what you can do with hand signals or ideograms or jpegs. A set of hand signals could convey a message much faster, but at the expense of loss of range, and easier misinterpretation. Spoken language trades bandwidth and information density for flexibility, nuance, and error tolerance. All major utilities when talking with a stranger, but not with our computers.

We keep chasing conversational interfaces in computing because of ease-of-access and the promise of flexibility. But in commanding the computer, the loss of compression, low bandwidth, and ambiguity are annoyances rather than assets. When we have a conversation with a clerk at the store, these are features. When it’s with our computers, they feel like bugs.

Julian goes on to talk about how we might think more creatively with fitting LLMs into this picture:

We spend too much time thinking about AI as a substitute (for interfaces, workflows, and jobs) and too little time about AI as a complement. Progress rarely follows a simple path of replacement. It unlocks new, previously unimaginable things rather than merely displacing what came before.

As AI seeps in everywhere, we need to think positive-sum in how it helps the human-computer interaction problem. It holds the potential to generate background threads of activity as we’re using our slow-but-flexible inputs like speech or typing: retrieving information and summarizing and performing interstitial actions while we’re in the middle of other tasks.

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MVPs with Cursor →

March 11, 2025 • #

Good stuff here on building with Cursor. Some takeaways:

Use starter kits to bootstrap project directories
Build assistive docs to help the Agent. Remember that the Agent behaves a lot like a human:
- A human with minimal guidance doesn’t infer the right choices
- PRDs, app flows, tech stacks / API docs, frontend/backend guidelines all help it do what you want
project rules over .cursorrules
- More flexible
- Sync across teams
- Fine-tune based on tech stack

I’ve had much better results getting in the weeds with PRDs well before having agents go off and build. And you can have multiple AIs work on and refine your documents, too.

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Expected and Unexpected →

March 6, 2025 • #

Some technologies are unpredicted, but evolve. Others are predicted don’t seem to materialize (or not yet). Then there are those that are expected AND appear. The unexpected tend to be the most disruptive — no one’s had the chance to prepare.

But the expected, if they do finally arrive, have been ruminated on for a long time. When we eventually realize the expected, we’re more prepared socially for their impacts. Though often we’re wrong about their societal impacts until they show up.

Kevin Kelly writes about this in the context of AI, a technology long-predicted, but always with a bent toward the negative. Toward the destructive social consequences of creating artificial beings.

Artificial beings – robots, AI – are in the Expected category. They have been so long anticipated that there has been no other technology or invention as widely or thoroughly anticipated before it arrived as AI. What invention might even be second to AI in terms of anticipation? Flying machines may have been longer desired, but there was relatively little thought put into imagining what their consequences might be. Whereas from the start of the machine age, humans have not only expected intelligent machines, but have expected significant social ramifications from them as well. We’ve spent a full century contemplating what robots and AI would do when it arrived. And, sorry to say, most of our predictions are worrisome.

Here’s the example list from Arthur C. Clarke’s 1963 book, Profiles of the Future:

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What Matters in the Age of AI is Taste →

February 24, 2025 • #

In this AI era, I’ve been thinking a lot about what it means for humans in the loop of formerly human tasks. When AI is inserted in all layers of the stack, what’s left for us?

Sari Azout hits on something I agree with: that the intangibles are (at least for now) resistant to AI. And these areas tend to be where we humans find joy in creativity in the first place. Taste, building context, intersecting divergent ideas, a respect for the tactile, the ephemeral, the unpredictable.

First, you need to cultivate a deeper relationship with your gut. The more our world becomes measurable and quantifiable, the more we need spaces that preserve what can’t be measured—the hunches we can’t explain, the patterns we feel but can’t prove. A jazz musician knows when to break rules in ways no theory explains. A good copywriter can feel what words will land without having a single data point to prove it. Taste isn’t some mysterious gift bestowed at birth—it’s simply what happens when you pay close attention to what moves you.

Our minds are good at finding patterns in the unquantifiable.

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Personal Software

January 17, 2025 • #

A common problem I encounter with computers is the everyday minor friction in workflow: the repetitive but only occasional task, or the tedious multi-step process.

Perfect example: the other day I wanted to batch resize and compress a bunch of images. It’s something I’ve had to do before, but not an everyday problem.

When you have a problem software can solve, it has to be painful enough to warrant the effort and overhead required to build something. Given my level of knowledge, I could thrash my way through writing a shell script to do this resizing operation (probably). But it’d take me a couple hours of Googling and trying and retrying to eventually get something that works — all for an operation that might take 7 minutes to just do manually. So rather than automate, I just deal with it.

This means dozens of daily nags go on nagging —they don’t nag enough to warrant the cost of solving. And they aren’t painful enough to search for and buy software to fix. So I go on muddling through with hacks, workarounds, and unanswered wishes.

But yesterday with a few prompts Cursor, in 15 minutes I made (or the AI made) a shell script to handle images that I can reuse next time. I didn’t even look at the code it wrote. Just typed 3 bullets of a description of what I wanted in a readme file, and out comes the code. An annoying process goes away, never having to search around for existing tools. Even if a solution did exist, it’d probably be part of a bundle of other features I don’t need; I’d pay for the Cadillac when I only need a taxi.

We’re moving into a new phase where personal software like this might often be the simplest path to a solution. In a world where we’re used to going to Google or GitHub, it’s now even faster to make your own. It’s cracked open new possibilities for people formerly incapable of creating their own tools.

Software used to be costly enough that those “hey this might be cool” ideas were quickly set aside when the cost/benefit wasn’t there. There’s potential for this new paradigm of digital goods production to radically alter the landscape of what gets built.

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August 23, 2024 • #

Prompt: “liminal space”

Recalls the finale of Interstellar.

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gpt-researcher →

June 19, 2024 • #

GPT Researcher is an autonomous agent designed for comprehensive online research on a variety of tasks.

The agent can produce detailed, factual and unbiased research reports, with customization options for focusing on relevant resources, outlines, and lessons. Inspired by the recent Plan-and-Solve and RAG papers, GPT Researcher addresses issues of speed, determinism and reliability, offering a more stable performance and increased speed through parallelized agent work, as opposed to synchronous operations.

I’ve been tinkering around with this tool for doing deeper topic research. It uses the ChatGPT API and GPT-4o to conduct multi-phase agent-based research. Adds sources, citations, and can be directed with specific tuning. Very interesting.

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February 16, 2024 • #

A periodic reminder of your pending competitive inadequacy - Marginal REVOLUTION →

Tyler Cowen:

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February 8, 2024 • #

A group of researchers just won the Scroll Prize, a project to read the ancient Herculaneum papyri, burned and buried in the eruption of Vesuvius in 79 AD.

Using AI and computer vision techniques they were able to discern text from the rolled, charred, and brittle papyrus. An unbelievable feat.

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The Vesuvius Challenge →

August 28, 2023 • #

Dr. Brent Seales, Nat Friedman, and Daniel Gross have launched a challenge: develop a computer vision algorithm to read and decode the Herculaneum scrolls.

Some background:

In Herculaneum, twenty meters of hot mud and ash bury an enormous villa once owned by the father-in-law of Julius Caesar. Inside, there is a vast library of papyrus scrolls.

The scrolls are carbonized by the heat of the volcanic debris. But they are also preserved. For centuries, as virtually every ancient text exposed to the air decays and disappears, the library of the Villa of the Papyri waits underground, intact.

Seales and his team have been working for years to develop a process to decode the scrolls without physical manipulation. Because they’re carbonized (think paper-thin charcoal), handling them pulverizes them into shards and dust. The latest AI boom shows promise to enable methods to finally decode the writing on these documents, using imaging techniques and CV.

Nat talked about this in depth during his interview a few months back with Dwarkesh Patel.

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Anachronistic History

August 24, 2023 • #

I asked ChatGPT:

Write about some creative anachronistic historical events.

The results don’t disappoint. Every single one is gold, big-budget film caliber material we got here. Scroll down and enjoy…

Marco Polo's Transcontinental Railroad, according to Midjourney

Leonardo’s Electric Canvas (1492): Leonardo da Vinci, known for his ingenious inventions, unveils the world’s first electrically powered canvas projector, allowing him to showcase his artwork in vibrant colors and dynamic animations, centuries ahead of its time.

Napoleon’s Moon Landing (1801): In a bid to establish a new world order, Napoleon Bonaparte orchestrates a daring expedition to the Moon using steam-powered spacecraft, setting the stage for lunar colonization and a galactic French empire.

Medieval Internet Symposium (1220): Scholars from across the medieval world gather for an “Internet Symposium,” where they discuss ideas through telepathic communication devices, resembling a rudimentary version of the internet.

Genghis Khan’s Airship Campaigns (1206-1227): Genghis Khan’s vast empire extends beyond land as his horde launches airborne campaigns using intricately designed airships, enabling swift conquests across continents with unprecedented speed.

Renaissance Era Robotics (1565): As a culmination of Renaissance curiosity, artisans and scientists collaborate to create a series of clockwork automatons that exhibit human-like intelligence and serve as precursors to modern robotics.

Cleopatra’s Underwater Expedition (50 BCE): Cleopatra, fascinated by the sea, leads a team of engineers and divers on an underwater archaeological expedition to explore the sunken city of Atlantis, unraveling ancient mysteries beneath the waves.

World War I: Age of Steampunk (1914-1918): The First World War takes on a different tone with both sides utilizing advanced steam-powered machinery, elaborate mechanical exosuits, and ornate weaponry, in a steampunk-inspired alternate history.

Marco Polo’s Transcontinental Railroad (1271-1295): Marco Polo’s extensive travels result in a collaborative effort among the nations he encountered to construct a massive transcontinental railroad network connecting Europe, Asia, and Africa centuries ahead of its time.

Industrial Revolution of Magic (1700s): The Industrial Revolution ushers in a new era of magic, where steam-driven wands power factories and alchemical engines replace conventional machines, driving technological progress through mystical means.

Joan of Arc’s Space Exploration (1429): Inspired by visions of the cosmos, Joan of Arc leads a celestial expedition using a fantastical flying fortress, journeying through the stars to bring harmony to distant planets.

Da Vinci’s Cyberspace Designs (1500): Leonardo da Vinci sketches out intricate plans for a virtual reality world using a combination of mirrors, lenses, and mechanical devices, offering a glimpse into a digital realm centuries ahead of its time.

Socrates’ Philosophical Podcast (399 BCE): Instead of written dialogues, Socrates engages in thought-provoking discussions through an ancient form of podcasting, spreading his philosophical ideas through the airwaves of Athens.

Ancient Egyptian Steam-Powered Pyramids (2500 BCE): The ancient Egyptians harness steam power to build their pyramids, using massive steam engines to lift and transport colossal stone blocks with astonishing precision.

Shakespearean Space Odyssey (1601): William Shakespeare’s play “Space Odyssey” tells the story of intrepid explorers venturing beyond Earth, grappling with cosmic conflicts and celestial dramas in a performance that takes theater to the stars.

Gutenberg’s Digital Printing Press (1450): Johannes Gutenberg invents a digital version of the printing press, allowing for instant creation and dissemination of books and manuscripts, revolutionizing information distribution long before the digital age.

Aztec Airborne Armada (1400s): The Aztecs develop an array of helium-filled airships, forming an airborne armada to defend their empire and launch surprise attacks on neighboring civilizations.

Ancient Greek Teleportation Symposium (300 BCE): Greek philosophers convene a “Teleportation Symposium,” discussing the ethics and implications of instantaneous travel across vast distances, shaping the course of human exploration.

Einstein’s Quantum Social Media Theory (1915): Albert Einstein introduces a theory of “Quantum Social Media,” predicting that interconnected networks of thoughts and ideas will shape the fabric of reality, long before the development of modern social platforms.

Viking Age Space Telescopes (800): Vikings construct massive, ornate space telescopes atop their ships, enabling them to explore distant planets and navigate the cosmos with extraordinary accuracy during their seafaring expeditions.

Caveman’s Cave-Painted Animation (10,000 BCE): Prehistoric artists create animated sequences on cave walls, employing ingenious mechanisms to bring their paintings to life and share stories through early forms of motion pictures.

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Patrick Collison and Sam Altman at Sohn 2023

May 10, 2023 • #

An interesting discussion between Patrick Collison and OpenAI founder Sam Altman on a predictably fascinating assortment of subjects. AI developments, stagnation, long-term bets, and what’s preventing us from having more founders.

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Against Safetyism →

April 26, 2023 • #

Byrne Hobart & Tobias Huber:

Over the past half-century, even leading AI researchers completely failed in their predictions of AGI timelines. So, instead of worrying about sci-fi paperclips or Terminator scenarios, we should be more concerned, for example, with all the diseases for which we weren’t able to discover a cure or the scientific breakthroughs that won’t materialize because we’ve prematurely banned AI research and development based on the improbable scenario of a sentient AI superintelligence annihilating humanity.

A great case for dynamism and progress as our best insulation against regulatory capture, risk, and exploitation.

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Census GPT →

April 24, 2023 • #

Census GPT is an open source tool put together by a new team working on product applications for GPT-4. It lets you write natural language questions to query the US Census database — things like the cities in Florida with the highest crime. It even shows the SQL output that GPT generates from your query.

Check out the project on GitHub, and join the their Discord to see what other kinds of datasets and use cases they’re tinkering with.

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Weekend Reading: Ancient Text, StarLink, and Chinese Origins

October 26, 2019 • #

📜 Restoring ancient text using deep learning: a case study on Greek epigraphy

A project from DeepMind designed to fill in missing text from ancient inscriptions:

Pythia takes a sequence of damaged text as input, and is trained to predict character sequences comprising hypothesised restorations of ancient Greek inscriptions (texts written in the Greek alphabet dating between the seventh century BCE and the fifth century CE). The architecture works at both the character- and word-level, thereby effectively handling long-term context information, and dealing efficiently with incomplete word representations (Figure 2). This makes it applicable to all disciplines dealing with ancient texts (philology, papyrology, codicology) and applies to any language (ancient or modern).

🛰 SpaceX submits paperwork for 30,000 more Starlink satellites

They’ve only launched 60 so far, but it looks like SpaceX has big plans for their future broadband satellite constellation.

🇨🇳 The People’s Republic of China Was Born in Chains

I haven’t read much Chinese history, but its origins and the Mao years were one of the greatest tragedies. And it’s frightening how much of that attitude is still there under the facade:

China today, for any visitor who remembers the country from 20 or 30 years ago, seems hardly recognizable. One of the government’s greatest accomplishments is to have distanced itself so successfully from the Mao era that it seems almost erased. Instead of collective poverty and marching Red Guards, there are skyscrapers, new airports, highways, railway stations, and bullet trains. Yet scratch the glimmering surface and the iron underpinnings of the one-party state become apparent. They have barely changed since 1949, despite all the talk about “reform and opening up.” The legacy of liberation is a country still in chains.

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mapwith.ai →

October 22, 2019 • #

In a conversation yesterday I learned about this project called RapiD, led by Facebook to use computer vision technology to detect features for mapping in OpenStreetMap. They’re working on a fork of the iD editor that does assistive feature detection to present an editor with generated geometries to add to the map. I messed around with it in the test areas they’re supporting so far and it’s a clever combination of computer-assisted detection and human-based mapping. This shows some promise to enhance OSM contributor technology and lower the barrier to entry for new editors.

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The Thousand Brains Theory of Intelligence →

July 5, 2019 • #

Most of the popular conversation around intelligence these days (at least in circles I follow) is about the artificial variety — AI, deep learning, neural networks, and the like. Neuroscientists Jeff Hawkins and his company Numenta have been studying intelligence since 2005, but oriented on how the brain itself works. Hawkins’s belief is that true “general AI” won’t be possible at all if we can’t first understand deeply how the brain works.

He recently published a paper on the “Thousand Brains Theory of Intelligence”, which posits that the brain is simultaneously generating predictions on multiple threads from different senses that it then assimilates to create models of the world:

To illustrate this concept in our newest paper, we use the example of a coffee cup. Imagine touching a coffee cup with one finger. As you move your finger over the cup, you sense different parts of it. You might feel the lip, then the curve of the handle, then the flatness of the bottom. Each sensation you receive is processed relative to its location on the cup. The curved handle of the mug is always in the same relative position on the cup; it is not a feature relative to you. At one moment it might be on your left and another moment on your right, but it is always in the same location on the cup. If you were asked to reach into a box and identify this object by touching it with one finger, you probably couldn’t with a single touch. But if you continued to move your finger over the object, you would integrate more sensory features from different locations, until you recognized with certainty that the only object containing this set of features at these locations is the coffee cup.

Now imagine the same mug, but this time you grasp it with multiple fingers at the same time. Whereas before you had to move your finger to recognize the cup, now you might be able to recognize it with a single grasp. The columns associated with each finger don’t have enough information on their own to identify the cup, but connections between columns allow them to reach the correct answer more quickly. In effect, the columns “vote” as to what is the most likely object, and quickly settle on cup. The same process occurs across senses, so cortical columns that process visual input can communicate with columns processing touch. In fact, there are connections in the cortex between low level sensory regions that don’t make sense in the classic hierarchical model of the cortex but do make sense in the Thousand Brains Theory.

Sandy sent me to this MIT AI podcast interview with Hawkins that goes deep on the Thousand Brains Theory and many other interesting related subjects of neuroscience and brain research.

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The Incredible Inventions of Intuitive AI

January 2, 2019 • #

This talk on “generative AI” was interesting. One bit stuck out to me as really thought-provoking:

Dutch designers have created a system to 3D print functional things in-place, like this bridge concept. Imagine that you can place a machine, give it a feed of raw material input and cut it loose to generate something in physical space. As the presenter mentions at the end of the talk, moving from things that are “constructed” to ones that are “grown”.

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