🚀Why Google Missed ChatGPT, Is fusion power 2 or 20 years away?, ChatGPT just killed take-home exams: 3 solutions, & more
Her avatars were pornified, while male colleagues got to be astronauts
Hi,
This is Thomas, Cofounder and CEO of digital agency KRDS (more about me at the end).
You're receiving Future Weekly, my personal selection of news about some of the most exciting (and sometimes scary) developments in technology 🤖 summarized as bullet points to help you save time and anticipate the future 🔮.
First, you'll find small bites about many different news, and then further down these summaries:
Read how Tesla is struggling like crazy with HR in Europe
A female tech writer tested the latest viral AI app Lensa that lets you create profile pictures from a few selfies, read what happened to her
ChatGPT just killed homework, essays, and take-home exams: 3 paths forward
2 examples of how Artificial intelligence is permeating business at last
Why Google Missed ChatGPT
What's the deal with fusion power? Decades away, or 2 years away?
Small Bites
Xioami built a humanoid robot that can play the drums
"The first reason Xiaomi is working on humanoid robots is that we are seeing a huge decline in the labor force in China, and the world." (source)
Seriously? Dyson has a weird $1k battery-powered headphone/face mask/air purifier (source)
"can capture up to 99% of the particle pollution, and carbon filters target gasses associated with city pollution, such as nitrogen dioxide and sulfur dioxide."
targets the Chinese market first and foremost
"The air filtration system can be detached from the headphones"
Crazy ChatGPT stories
Wow: this doctor shows in that 2-min video how he’s getting ChatGPT to write a well-written letter with scientific references to persuade an insurance company to cover an expense that quite often is not, simply asking: "Write a letter to United healthcare asking them to approve an Echocardiogram on a patient with Systemic Sclerosis. Make references to supporting scientific literature. List the appropriate articles."
Someone got ChatGPT to generate a: 💡Movie Concept, 🗺️ Plot, 🤖 Character Bio and 🎬 Sequel, all in 11 messages, and then Stable Diffusion to "design" 🖌️ Concept Art for it (source)
Someone, not particularly tech-minded, wrote a half-decent Excel tool with it that saved him a few hours at work” (source)
He works in higher education, studied English at university, and never formally learned to code.
But here he was, not only playing around with an experimental AI chatbot but using it to do his job faster after only a few days’ access.
“I asked it some questions, asked it some more, put it into Excel, then did some debugging,” is how he described the process. “It wasn’t perfect but it was easier than Googling.”
An author showing how ChatGPT could completely disrupt their industry (source with actual examples)
I put together a demo in 2 minutes, showing that ChatGPT can come up with ideas of novels in seconds across a range of genres.
ChatGPT can come up with your main characters, your storyline, and more for you, all with incredible ease
Finally, if you can't be bothered actually writing the thing, ChatGPT will get started for you. It does a surprisingly good job of this, and no doubt the technology will continue to improve.
It will even compose an e-mail to an agent for you pitching the book. This is science fiction, folks. And, I haven't even scratched the surface when it comes to writing scenes.
He shares more examples of ChatGPT writing engaging fiction in real-time, without pausing to think or having to research the topic. Here, it tackles historical fiction and crime fiction, two completely different genres, with ease. And remember, this is just the beta version.
"I spent the weekend playing with ChatGPT, MidJourney, and other AI tools… and by combining all of them, published a children’s book co-written and illustrated by AI!" (Detailed here)
Read the answer to the prompt: "Write a biblical verse explaining how to remove a peanut butter sandwich from a VCR"
The bones of ChatGPT are not entirely new (it’s based on GPT-3.5, a large language model that was released by OpenAI this year but which itself is an upgrade to GPT-3, from 2020). OpenAI has previously sold access to GPT-3 as an API, but the company’s ability to improve the model’s ability to talk in natural dialogue and then publish it on the web for anyone to play with brought it to a much bigger audience. And no matter how imaginative AI researchers are in probing a model’s skills and weaknesses, they’ll never be able to match the mass and chaotic intelligence of the internet at large.
🤯 OpenAI is rumored to launch GPT-4 as soon as in 2023, with 500 times more parameters than GPT-3, a proxy for how much better it may work
This tool sumup.page will summarize an article, just enter a link. Very easy to test, free, no registration
Finding this interesting? ❤️
If yes, feel free to take 3 seconds to forward that newsletter to one person, I'd be immensely grateful 🙂
If that email was forwarded to you, you can click here to subscribe and make sure to receive future editions in your mailbox (many CEOs and startup founders are subscribers)
More to chew!
Tesla is struggling with HR in Europe: Tesla’s Berlin Hub Can’t Hire Enough People, or Keep Them (Wired)
according to former and current employees at the gigafactory, current staffers are leaving jobs due to low and unequal pay and inexperienced management in the highly competitive German manufacturing sector
One current employee, who requested anonymity out of fear of losing their job, describes the Berlin gigafactory as “total chaos.” “Some people are off sick longer than they’ve actually worked. There are people who I haven’t seen working for three weeks in six months.
People in HR want to hit their targets for recruitment, so they will say anything to get people in, but not pay attention to keeping these workers,” they say.
"unannounced changes in working conditions."
Tesla’s attempt to improve recruitment and retention by increasing pay for new staff also backfired, as longer-term employees were being paid less than employees who had just arrived doing the same jobs with similar qualifications.
A female tech writer tested the latest viral AI app Lensa that lets you create profile pictures from a few selfies (source)
"I was hoping to get results similar to my colleagues at MIT Technology Review. The app generated realistic and flattering avatars for them—think astronauts, warriors, and electronic music album covers."
"Instead, I got tons of nudes. Out of 100 avatars I generated, 16 were topless, and another 14 had me in extremely skimpy (short and revealing) clothes and overtly sexualized poses."
Lensa generates its avatars using Stable Diffusion, an open-source AI model that generates images based on text prompts. Stable Diffusion is built using a massive open-source data set that has been compiled by scraping images off the internet.
And because the internet is overflowing with images of naked or barely dressed women, and pictures reflecting sexist, racist stereotypes, the data set is also skewed toward these kinds of images
The company says that because Stable Diffusion is trained on unfiltered data from across the internet, neither they nor Stability.AI, the company behind Stable Diffusion, “could consciously apply any representation biases or intentionally integrate conventional beauty elements.”
ChatGPT just killed homework, essays, and take-home exams: 3 paths forward (source)
Apps to answer math questions have been around for a while.
But ChatGPT is different - it can do things that previously required human judgment and analysis, like writing full essays or solving complex problem sets.
The result? An "existential crisis" for educators.
3 paths forward:
1. Schools adjust assignments to prevent the use of AI.
Take-home work largely disappears. Class time is used for proctored essays, problem sets, and exams.
Homework time is spent learning asynchronously via video - a "flipped classroom" model.
(this is the method used by the sucessful online Khan Academy for years)
2. Schools embrace AI.
Students will use AI in real life. Why make them do things the "old fashioned way" at school?
Instead, lessons will incorporate AI - teaching students how to write prompts, analyze outputs, and edit as needed
3. Schools learn to audit AI.
In this case, AI assistance is viewed like plagiarism. Educators learn how to detect it, and have policies in place to downgrade or disqualify assignments.
A "GPT watermark" may already be in the works at OpenAI
An investor tweeted (and then deleted)
Society is not ready for a step function inflection in our ability to costlessly produce anything connected to text. Human morality does not move that quickly, and it’s not obvious how we now catch up.
I am hearing from colleges unsure what to do about grading ALL ESSAYS this term. Hundreds and hundreds of essays. The examples are legion across many, many domains. A societal trust collapse, at scale. I obviously feel ChatGPT (and its ilk) should be withdrawn immediately.
2 examples of how Artificial intelligence is permeating business at last (The Economist)
agriculture
This autumn John Deere, a tractor-maker, shipped its first fleet of fully self-driving machines to farmers. The tilling tractors are equipped with six cameras which use artificial intelligence (AI) to recognise obstacles and manoeuvre out of the way.
50% of the vehicles John Deere sells have some AI capabilities. That includes systems which use onboard cameras to detect weeds among the crops and then spray pesticides, and combine harvesters which automatically alter their own setting to waste as little grain as possible.
For a medium-sized farm, the additional cost of buying an AI-enhanced tractor is recouped in 2 to 3 years.
programming
A number of firms are offering a virtual assistant trained on a large deposit of code that churns out new lines when prompted.
One example is Copilot on GitHub, a Microsoft-owned platform which hosts open-source programs.
Programmers using Copilot outsource nearly 40% of the code-writing to it. This speeds up programming by 50%, the firm claims.
Why Google Missed ChatGPT (source)
After years of preaching that conversational search was its future, it’s stood by as the world discovered ChatGPT.
This was the future Google promised. But not with someone else fulfilling it.
“Google thinks a lot about how something can damage its reputation,” said Gaurav Nemade, an ex-Google product manager who was first to helm its LaMDA chatbot. “They lean on the side of conservatism.”
Google’s LaMDA — made famous when engineer Blake Lemoine called it sentient earlier in June 2022— is a more capable bot than ChatGPT, yet the company’s been hesitant to make it public.
For Google, the problem with chatbots is they’re wrong a lot, yet present their answers with undeserved confidence. Leading people astray — with assuredness — is less than ideal for a company built on helping you find the right answers. So LaMDA remains in research mode.
On the one hand, a sophisticated, public chatbot like ChatGPT makes waiting for the perfect business model risky. Delay long enough, and you could cede the market.
On the other hand, ChatGPT will also take criticism as it gains adoption, sustaining hits that otherwise would’ve been Google’s. ChatGPT’s shortcomings will teach people to view its certainly with skepticism, clearing the way for a risk-averse Google to release its own version.
For now, ChatGPT’s threat to Google remains somewhat limited. The bot doesn’t access the internet, knows nothing beyond 2021 (or at least, it says so), costs a few cents per chat to OpenAI, and has no ads. So while it may take some traditional queries away from Google, it won’t push the $1.2 trillion company to the brink. At least as presently constituted.
But things could change in a hurry. Should OpenAI connect ChatGPT to the internet, it could push Google to bring its own product to market, and its vision for the future along with it. And once Google gets involved, those who’ve seen its chatbot technology expect it to win.
“If ChatGPT or some other product ever became a real threat,” said Lemoine, “they'd just bite the bullet and release LaMDA, which would smoke ChatGPT.”
What's the deal with fusion power? Decades away, or 2 years away?
Nuclear fusion is a man-made process that replicates the same energy that powers the sun. Nuclear fusion happens when two or more atoms are fused into one larger one, a process that generates a massive amount of energy as heat. That heat can be used to warm water, create steam and turn turbines to generate power – much like how nuclear fission generates energy.
Scientists around the world have been studying nuclear fusion for decades, hoping to recreate it with a new source that provides limitless, carbon-free energy – without the long-lived nuclear waste created by current nuclear reactors. Fusion projects mainly use the elements deuterium and tritium – both of which are isotopes of hydrogen
Hydrogen isotopes are atoms of hydrogen with different numbers of neutrons in their nuclei, respectively 1 and 2 neutrons for deuterium and tritium, in addition to the only one proton that defines the hydrogen atom
The deuterium from a glass of water, with a little tritium added, could power a house for a year. Tritium is rarer and more challenging to obtain, although it can be synthetically made. A small cup of the hydrogen fuel could theoretically power a house for hundreds of years.
Physicists have since the 1950s sought to harness the fusion reaction that powers the sun, but no group had been able to produce more energy from the reaction than it consumes.
On December 5, researchers at the Lawrence Livermore Lab’s National Ignition Facility (NIF) finally took the perfect shot: this is the first time scientists have ever successfully produced a nuclear fusion reaction resulting in a net energy gain, instead of breaking even as in past experiments.
2 megajoules in (the energy used in 15 minutes of running a hair dryer, but delivered all at once, in a millionth of a second) & 3 megajoules out. A 50% gain of energy.
The difference is in how scientists define breakeven. Today, the NIF researchers said they got more energy out than their laser fired at the experiment
But the problem is that the energy in those lasers represents a tiny fraction of the 200 megajoules involved in firing up those lasers. By that measure, NIF is getting way less than they’re putting in. “The real type of breakeven is way, way, way, way down the road,” Cappelli says. “That’s decades down the road. Maybe even a half century down the road.”
Generating fusion energy using NIF’s method involves shooting dozens of laser beams into a gold cylinder, heating it up to more than 3 million °C. The lasers don’t target the fuel directly. Instead, their aim is to generate “a soup of x-rays.” These bombard the tiny pea-sized fuel pellet consisting of the hydrogen isotopes deuterium and tritium, and crush it.
The compression caused by the beams (or, rather, by x-rays generated by their effect on the capsule containing the pellet) overcomes the mutual electrical repulsion of the nuclei of the atoms in the pellet, which are all positively charged. It thereby pushes those nuclei close enough to one another for a different fundamental force, the strong nuclear force (which operates only at short ranges) to take over.
The trouble is inefficient lasers. Producing those laser beams at NIF involves a space nearly the size of a football field built at a cost $3.5 billion, filled with flashing lamps that excite the laser rods and propagate the beams. That alone takes 300 megajoules of energy, most of which is lost.
Add to that layers of cooling systems and computers, and you quickly get an energy input that’s multiple orders of magnitude greater than the energy produced by fusion.
To produce sustained energy, scientists need to figure out how to repeatedly fire the powerful lasers and get many pellets in front of them. That could involve multiple pellets and laser firings per minute. By comparison, NIF currently fires 3 times per day.
This type of fusion experiment with laser beams is known as “inertial confinement", it has gotten less attention than another type of fusion technology known as “magnetic confinement” which involves a donut-shaped device known as a tokamak, in which hydrogen gas is heated into plasma and then trapped by magnetic fields. Commercial fusion companies have generally taken the magnet route, as has ITER, in part because of the challenges of lasers. But recently, inertial facilities have seen more investment—and today’s success may mean more of that ahead.
The Economist is harsher: It seems unlikely that the future of civil fusion power (if it has one) lies with inertial-confinement by laser. The technology is fiddly. And even with lasers more modern than that used by NIF (which opened in 2009) the process of “pumping” the device to create the beam is inherently inefficient. None of the increasingly numerous attempts to commercialise fusion employs inertial-confinement by laser. Most are based on tokamaks.
Despite today’s announcement, fusion is neither commercial nor close to commercial, so it is still vaporware,” says Mark Jacobson, an energy researcher at Stanford who has argued for more investment in available solutions like solar, wind, and hydropower. Indeed, you would be hard-pressed to find a plasma physicist who thinks fusion will be in the mix in the next decade.
Sources: Wired, The Economist.
But...now we have a way to produce fusion “fire” on demand. The knowledge we will gain from this capability will greatly benefit all other fusion efforts
And…
Sam Altman, CEO d'OpenAI, invested $375 million in Helion, "his largest investment in a start-up ever":
“by far the most promising approach to fusion I’ve ever seen,” said Altman in November 2021. “With a tiny fraction of the money spent on other fusion efforts, and the culture of a startup, this team has a clear path to net electricity. If Helion is successful, we can avert climate disaster and provide a much better quality of life for people.”
July 2022 update, Sam Altman said:
"Helion has been progressing even faster than I expected and is on pace in 2024 to 1) demonstrate fusion with a net energy gain and 2) resolve all questions needed to design a mass-producible fusion generator."
"The goals of the company are quite ambitious—clean, continuous energy for 1 cent per kilowatt-hour, and the ability to manufacture enough power plants to satisfy the current electrical demand of earth in a ten-year period."
Previous newsletters:
That's it for this week :)
If you made it until here, well, thanks a lot for reading this newsletter! A very simple way to encourage me to continue doing this is to take a few seconds to:
share this with a curious friend
click on the little star next to that email in your mailbox
click on the heart at the bottom of that email
Thank you so much in advance! 🙏
Here to subscribe to make sure you get the future editions if this one was forwarded to you.
More about me
I cofounded KRDS right after college back in 2008 in Paris, we now also have offices in Singapore, HK, Shanghai, Dubai and India, we're one of the largest independent digital agencies in Asia. More here.
I launched 2 sister agencies:
OhMyBot.net, dedicated to designing and building chatbots
The WeChat Agency for the Chinese market
I also write op-eds and do podcasts at times. Here are my latest articles and podcasts
For the French speakers:
I’ve written more than 50 articles on the future of technology over the past years, all can be found listed here.
This newsletter has a French version with slightly different content: Parlons Futur
Have a great week ahead :)
Thomas