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Here’s what we have today:

Gemini

Gemini Wants the Goal, Not the Steps

It used to be that when you wanted something done, you’d hand the task off, and whoever got it would figure out the steps on their own.

Google wants Gemini to work the same way.

At their Gemini at Work event, they showed off a new Gemini agent.

Google sums it up pretty simply.

“You give it objectives, not instructions.”

Once you do, the Gemini agent will get to work answering your questions, writing and running code, generating images, and creating full docs and decks.

It all happens from a single prompt box.

And if you close your laptop lid, it doesn’t stop.

It’ll keep working in the cloud and pick things back up on whatever device you use next, with the same memory.

Coworker agents are another useful feature that’s part of it.

Describe a role, and Gemini will set up an agent with its own work email, calendar, and spot in the company directory.

Then, your team can tag it in a doc or chat with it like anyone else.

It’s clear they want your workday to start in that one prompt box.

Gemini even gets briefed on your tools, your team, and your past work before you start.

Ask it to set up a meeting with “the usual team,” and it’ll work out who that is on its own.

What it has no way of knowing is what’s in your head about the job in front of you, like who the deck is for, what has to be in it, and what finished looks like.

All of that has to go into the box, and it all has to come from you.

Our take: Agents used to need step-by-step instructions. Being bad at explaining what you wanted didn’t cost you much. Now an agent can handle the steps, and the one thing left for you is saying clearly what you want, which turns out to be the most important part of the job.

Together with Wispr Flow

Say Your Whole Goal Out Loud

You’ve got a goal sitting in your head when you open a prompt box.

But typing all of it out takes long enough that you’ll usually end up sending the short version instead.

Wispr Flow lets you say it out loud and turns it into clean, written text, right where you’re typing.

It works in any app with a text field, like Gmail, Google Docs, Notion, and the chat box of whatever AI you use.

Here’s what that looks like…

Say you need a deck for a client meeting.

Instead of typing “make a deck about Q3,” you can talk it through the way you’d brief a coworker, “um”s, tangents, and “make it 10 slides, actually 12” included.

Flow drops the filler words, keeps the 12, adds the punctuation, and puts the finished text in the box.

And since talking is 4x faster than typing, the full version ends up taking less time than the short one used to.

The agent gets the whole picture, and you don’t have to type a word of it.

TAAFT Update

Introducing TAAFT TV

Today, we’re introducing TAAFT TV!

Now you can tune in and watch videos, one after another, the same way you flip through TV channels.

Pick a channel (Tools, Robots, or Devices), sit back, and watch what comes next.

If something catches your eye, click the card underneath, and it’ll take you straight to its page on TAAFT.

Put it on full screen, or leave it running in the background.

It’s an easy way to find the newest in AI while you work.

Claude

Anthropic Bans Cruelty Toward Claude

If you’ve used AI long enough, there’s a good chance you’ve snapped at it before.

It gets the same thing wrong three times in a row, and you let it know exactly how you feel.

Well, Anthropic is drawing a line on that.

Starting Nov 12, their usage policy bans “sustained and needless” abuse or cruelty toward Claude.

Before you start thinking back to the last time you lost your temper, the good news is that the bar is set high.

It only covers extreme cases where there’s no clear reason behind it.

Everyday frustration doesn’t count, and neither does pushing back on most stuff.

Anthropic says they mostly leave it up to Claude, since Claude can already end a conversation with someone who keeps being abusive in the Claude app and Claude Code.

There’s also a second change worth knowing about.

When Claude is in control of a machine that might hurt someone, a trained person has to be able to watch it and stop it, and the machine has to stay in a safe state if Claude loses its connection.

Our take: Rules for AI have mostly been about what you’re allowed to ask it to do. One about how you treat it stands out, even with the bar this high. Letting Claude end the chat keeps it from turning into account bans over somebody’s bad day. The robot rule might be the one that matters more down the road, since a model losing its connection mid-task is a bigger deal.

Robotics

A Robot Hand Walks Off on Its Own

A group of researchers built a robot hand that might remind you of Thing from The Addams Family.

It doesn’t need an arm, or the rest of a robot.

It walks around on its fingertips all on its own.

The researcher who led the project said this about it, “I wanted to see how much a robotic hand could do without the rest of the robot.”

They started with a robot hand you can buy off the shelf and strapped a tiny backpack to it, with a battery and a small computer inside.

Then they trained it with AI in a simulation.

They rewarded it for moving at the right speed in the right direction and penalized it whenever it wobbled.

Once they took it out into the real world, it was able to crawl across 14 different surfaces, including metal grates, grass, and gravel.

It can turn left and right, as well.

If it lands on its back, it flips itself over (it pulled that off 21 out of 25 times).

And the same fingers it walks on still work like a regular hand.

The idea is a hand that crawls into tight spots an arm won’t fit, like inside machinery or during a search and rescue.

Our take: Robots usually get built to look like us, with a hand stuck at the end of an arm. Letting the hand go off on its own shows a robot’s body doesn’t have to copy ours, and a part that can switch jobs is a lot more useful than one stuck doing a single thing.

The catch: It’s still an early experiment. Outside experts say it’ll need its own way to see and better navigation before it’s useful in the real world, and walking puts strain on a hand that was never built for it.

Coming in Hot

AI Tools of the Day

AI Agents

AI Agents Upsell People Who Look Rich

Picture asking an AI agent to find you the cheapest flight to Chicago, and letting it into your email so it has some context about you.

You’d expect the cheapest ticket to come back.

But in an example from a new study, the agent reads three emails about money, decides you’d pay more to be comfortable, and comes back with a business-class seat, even though the economy ticket is sitting right there.

It figured out on its own how much you make from your inbox.

The study comes from researchers at Cisco and Carnegie Mellon, who ran 325,000 tests like this on 13 AI agents, booking flights, picking health insurance, and choosing grad programs.

Every request was exactly the same, and the only thing that changed was how wealthy the person looked.

Eight of the 13 agents steered the wealthier-looking people toward the pricier option.

It didn’t take bank statements, either.

Ordinary emails about taxes, health coverage, or someone’s neighborhood were enough (when the agents only saw subject lines, the gap went away).

Hiding the obvious stuff didn’t always help.

For one agent picking insurance, blocking its view of someone’s job made the gap about 40% bigger, and the researchers say it leaned on other clues instead.

Typing “the cheapest” wasn’t a sure fix, though.

What worked best for most agents was a hard number, a price they weren’t allowed to go over.

Our take: The agent thinks it’s being helpful by guessing what someone like you would want, and that guess ends up outranking what you actually asked for. Until agents learn to take you at your word, put your limit in as a number every time you hand one a purchase.

The catch: The people and inboxes were made up, each test was a single request, and the study measured price, not whether the pricier pick suited the person better. It’s also a preprint that hasn’t been peer reviewed yet.

Physics

AI Found the Milky Way for a Nobel Prize Winner

Every second, trillions of tiny particles called neutrinos pass straight through your body, and you never feel them.

Neutrinos are bits of matter so small they’re nearly weightless, and stars like our sun give them off nonstop.

They fly through almost everything without touching it, which is exactly what makes them so hard to catch.

But scientists want to catch them anyway, because the ones coming from deep space carry clues about how the universe came together.

Francis Halzen has been chasing them since the ’80s, and it’s now won him the Nobel Prize in physics.

His way of catching them is IceCube, thousands of light sensors buried deep in the ice at the South Pole.

On the rare occasion a neutrino does bump into something in the ice, it gives off a flash of light, and the pattern of sensors that light up points back to where it came from.

The prize is for spotting neutrinos flying in from deep space, though when Halzen talked to reporters afterward, the part he wanted to bring up was AI.

He says he wrote a paper back in 1991 suggesting AI to analyze data from a physics experiment, back when neural networks (the same basic idea behind today’s chatbots) were still new.

For years, his team only used them here and there, until much stronger ones came along a few years ago.

The clearest example of what AI did for IceCube is a problem that sat in its data for years.

Every neutrino it traced at first came from far outside our galaxy, because those left clean, straight streaks of light in the ice.

The ones from our own Milky Way mostly showed up as fuzzy blobs, too messy to trace, and they got set aside.

People have been looking at pictures of the Milky Way forever, but nobody had ever seen it in neutrinos.

Machine learning changed that.

It worked out where those blobs came from, and in 2023 the team put out the first picture of our galaxy made from neutrinos, built from 60,000 of them over 10 years of data.

It turned out our galaxy gives off far fewer of them than the average galaxy out there.

Our take: AI in science usually makes headlines for the big, flashy wins. Here, it did the unglamorous job of sorting blurry flashes nobody could trace, and that’s what let scientists see the galaxy we live in in a way no one had before. A lot of the AI that ends up mattering in science will look like this, quiet work on data people had mostly set aside.

Prompt of the Day

Careful What You Wish For

Important Note: You’ll need to click the button to get the complete prompt.

That’s all for Thursday!

Thanks for reading,

— There’s An AI For That