Sam Altman is a habitual liar and can't be trusted, says former OpenAI board member

bnew

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1/2
@jaminball
If you add the current 4o-mini pricing to the chart, the drop in token pricing is 99.7% over last 18 months!

For everyone nervous about the real-time audio pricing being ~$120 / 1m tokens, take comfort in the below chart. This price will undoubtedly come down significantly!

[Quoted tweet]
OpenAI has shared this chart a few times, but important to call out. Inference pricing on GPT4 family of models has dropped nearly 90% since it's release!

This trend will continue. Business models that don't make sense now will in the future. Latent demand will be unlocked.


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2/2
@BrianBrechbuhl
This was before raising $7B though!




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Professor Emeritus

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You got Nobel Prize winners in AI shytting on Sam Altman now






“I was particularly fortunate to have many very clever students – much cleverer than me – who actually made things work,” said Hinton. “They’ve gone on to do great things. I’m particularly proud of the fact that one of my students fired Sam Altman.”

"So OpenAI was set up with a big emphasis on safety. Its primary objective was to develop artificial general intelligence and ensure that it was safe," Hinton said on Tuesday.

"And over time, it turned out that Sam Altman was much less concerned with safety than with profits. And I think that's unfortunate," he added.
 

bnew

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1/11
@johnschulman2
I shared the following note with my OpenAI colleagues today:

I've made the difficult decision to leave OpenAI. This choice stems from my desire to deepen my focus on AI alignment, and to start a new chapter of my career where I can return to hands-on technical work. I've decided to pursue this goal at Anthropic, where I believe I can gain new perspectives and do research alongside people deeply engaged with the topics I'm most interested in. To be clear, I'm not leaving due to lack of support for alignment research at OpenAI. On the contrary, company leaders have been very committed to investing in this area. My decision is a personal one, based on how I want to focus my efforts in the next phase of my career.

I joined OpenAI almost 9 years ago as part of the founding team after grad school. It's the first and only company where I've ever worked, other than an internship. It's also been quite a lot of fun. I'm grateful to Sam and Greg for recruiting me back at the beginning, and Mira and Bob for putting a lot of faith in me, bringing great opportunities and helping me successfully navigate various challenges. I'm proud of what we've all achieved together at OpenAI; building an unusual and unprecedented company with a public benefit mission.

I am confident that OpenAI and the teams I was part of will continue to thrive without me. Post-training is in good hands and has a deep bench of amazing talent. I get too much credit for ChatGPT -- Barret has done an incredible job building the team into the incredibly competent operation it is now, with Liam, Luke, and others. I've been heartened to see the alignment team coming together with some promising projects. With leadership from Mia, Boaz and others, I believe the team is in very capable hands.

I'm incredibly grateful for the opportunity to participate in such an important part of history and I'm proud of what we've achieved together. I'll still be rooting for you all, even while working elsewhere.



2/11
@sama
Thank you for everything you've done for OpenAI! You are a brilliant researcher, a deep thinker about product and society, and mostly, you are a great friend to all of us. We will miss you tremendously and make you proud of this place.

(I first met John in a cafe in Berkeley in 2015. He said something like "on one hand it seems ridiculous to be talking about AGI right now, but on the other hand I think it's very reasonable and here is why and also here is why I think it's important to be talking about it" and then laid out a significant fraction of what became OpenAI's initial strategy. That took about 15 minutes and then we awkwardly chatted for another 45 :smile: )



3/11
@Kat__Woods
Can you clarify? Sounds like you're saying that you're leaving the safety team so you can focus on safety.

But also, you say that you got support for researching safety?



https://video.twimg.com/ext_tw_video/1820626304045371392/pu/vid/avc1/720x720/_TxdtgItXWQX4chn.mp4

4/11
@LearnAI_MJ
GPT-5: I also quit 👋



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5/11
@iamgingertrash
And thus it was foretold - the inevitable demise of OpenAI as the elves left for greener pastures



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6/11
@ChrisUniverseB
"To be clear, I'm not leaving due to lack of support for alignment research at OpenAI. On the contrary, company leaders have been very committed to investing in this area. My decision is a personal one, based on how I want to focus my efforts in the next phase of my career."

I heard that 2 months ago leadership repeatedly denied access to compute resources which are very critical in developing new AI safety schemes so idkkkkk



7/11
@psychosort
Congratulations, and all the best going forward!



8/11
@alexalbert__
Welcome to the team, John!



9/11
@AISafetyMemes




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10/11
@yacineMTB
anthropic is great! I love the research and the people are great. Good luck and work hard 🙏



11/11
@janleike
Very excited to be working together again!




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1/11
@Luke_Metz
I'm leaving OpenAI after over 2 years of wild ride.

Alongside @barret_zoph , @LiamFedus , @johnschulman2 , and many others I got to build a “low key research preview” product that became ChatGPT. While we were all excited to work on it, none of us expected it to be where it is today, 100s of millions of users in a historically short amount of time. It was truly a privilege to witness its growth.

I learned so much through the process. Thank you so much @sama , @gdb , @miramurati , @ilyasut, @bobmcgrewai for giving us a chance. OpenAI is a special place.

Now, onto new things!



2/11
@chipro
What a ride! Can't wait to see what you'll build next



3/11
@nearcyan
thank you for the amazing work, looking forward to the future!



4/11
@stevenheidel
I always learned something new every time we had lunch, best of luck with what’s next!



5/11
@dhruv2038
OpenAi is nothing without it's people.



6/11
@austinvhuang
appreciated your onboarding tips back when i was starting at brain and you were on your way to oai.

good luck with what's next.



7/11
@ericjang11
Excited to see what you’ll do next!



8/11
@victor_explore
How much of the reason was burnout?



9/11
@stallion1319
First of all Good luck Luke and you guys did an incredible achievement, now why is everyone leaving ?🥸



10/11
@horsperg
Thanks, and may the wind be on your back!



11/11
@keshab001
Everyone leaving to launch their own company that will earn them more money




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bnew

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Moore's Law for Everything​

by Sam Altman · March 16, 2021

My work at OpenAI reminds me every day about the magnitude of the socioeconomic change that is coming sooner than most people believe. Software that can think and learn will do more and more of the work that people now do. Even more power will shift from labor to capital. If public policy doesn’t adapt accordingly, most people will end up worse off than they are today.

We need to design a system that embraces this technological future and taxes the assets that will make up most of the value in that world–companies and land–in order to fairly distribute some of the coming wealth. Doing so can make the society of the future much less divisive and enable everyone to participate in its gains.

In the next five years, computer programs that can think will read legal documents and give medical advice. In the next decade, they will do assembly-line work and maybe even become companions. And in the decades after that, they will do almost everything, including making new scientific discoveries that will expand our concept of “everything.”

This technological revolution is unstoppable. And a recursive loop of innovation, as these smart machines themselves help us make smarter machines, will accelerate the revolution’s pace. Three crucial consequences follow:

  1. This revolution will create phenomenal wealth. The price of many kinds of labor (which drives the costs of goods and services) will fall toward zero once sufficiently powerful AI “joins the workforce.”
  2. The world will change so rapidly and drastically that an equally drastic change in policy will be needed to distribute this wealth and enable more people to pursue the life they want.
  3. If we get both of these right, we can improve the standard of living for people more than we ever have before.

Because we are at the beginning of this tectonic shift, we have a rare opportunity to pivot toward the future. That pivot can’t simply address current social and political problems; it must be designed for the radically different society of the near future. Policy plans that don’t account for this imminent transformation will fail for the same reason that the organizing principles of pre-agrarian or feudal societies would fail today.

What follows is a description of what’s coming and a plan for how to navigate this new landscape.

Part 1

The AI Revolution​


On a zoomed-out time scale, technological progress follows an exponential curve. Compare how the world looked 15 years ago (no smartphones, really), 150 years ago (no combustion engine, no home electricity), 1,500 years ago (no industrial machines), and 15,000 years ago (no agriculture).

The coming change will center around the most impressive of our capabilities: the phenomenal ability to think, create, understand, and reason. To the three great technological revolutions–the agricultural, the industrial, and the computational–we will add a fourth: the AI revolution. This revolution will generate enough wealth for everyone to have what they need, if we as a society manage it responsibly.

The technological progress we make in the next 100 years will be far larger than all we’ve made since we first controlled fire and invented the wheel. We have already built AI systems that can learn and do useful things. They are still primitive, but the trendlines are clear.

Part 2

Moore's Law for Everything​


Broadly speaking, there are two paths to affording a good life: an individual acquires more money (which makes that person wealthier), or prices fall (which makes everyone wealthier). Wealth is buying power: how much we can get with the resources we have.

The best way to increase societal wealth is to decrease the cost of goods, from food to video games. Technology will rapidly drive that decline in many categories. Consider the example of semiconductors and Moore’s Law: for decades, chips became twice as powerful for the same price about every two years.

In the last couple of decades, costs in the US for TVs, computers, and entertainment have dropped. But other costs have risen significantly, most notably those for housing, healthcare, and higher education. Redistribution of wealth alone won’t work if these costs continue to soar.

AI will lower the cost of goods and services, because labor is the driving cost at many levels of the supply chain. If robots can build a house on land you already own from natural resources mined and refined onsite, using solar power, the cost of building that house is close to the cost to rent the robots. And if those robots are made by other robots, the cost to rent them will be much less than it was when humans made them.

Similarly, we can imagine AI doctors that can diagnose health problems better than any human, and AI teachers that can diagnose and explain exactly what a student doesn’t understand.

“Moore’s Law for everything” should be the rallying cry of a generation whose members can’t afford what they want. It sounds utopian, but it’s something technology can deliver (and in some cases already has). Imagine a world where, for decades, everything–housing, education, food, clothing, etc.–became half as expensive every two years.

We will discover new jobs–we always do after a technological revolution–and because of the abundance on the other side, we will have incredible freedom to be creative about what they are.

Part 3

Capitalism for Everyone​


A stable economic system requires two components: growth and inclusivity. Economic growth matters because most people want their lives to improve every year. In a zero-sum world, one with no or very little growth, democracy can become antagonistic as people seek to vote money away from each other. What follows from that antagonism is distrust and polarization. In a high-growth world the dogfights can be far fewer, because it’s much easier for everyone to win.

Economic inclusivity means everyone having a reasonable opportunity to get the resources they need to live the life they want. Economic inclusivity matters because it’s fair, produces a stable society, and can create the largest slices of pie for the most people. As a side benefit, it produces more growth.

Capitalism is a powerful engine of economic growth because it rewards people for investing in assets that generate value over time, which is an effective incentive system for creating and distributing technological gains. But the price of progress in capitalism is inequality.

Some inequality is ok–in fact, it’s critical, as shown by all systems that have tried to be perfectly equal–but a society that does not offer sufficient equality of opportunity for everyone to advance is not a society that will last.

The traditional way to address inequality has been by progressively taxing income. For a variety of reasons, that hasn’t worked very well. It will work much, much worse in the future. While people will still have jobs, many of those jobs won’t be ones that create a lot of economic value in the way we think of value today. As AI produces most of the world’s basic goods and services, people will be freed up to spend more time with people they care about, care for people, appreciate art and nature, or work toward social good.

We should therefore focus on taxing capital rather than labor, and we should use these taxes as an opportunity to directly distribute ownership and wealth to citizens. In other words, the best way to improve capitalism is to enable everyone to benefit from it directly as an equity owner. This is not a new idea, but it will be newly feasible as AI grows more powerful, because there will be dramatically more wealth to go around. The two dominant sources of wealth will be 1) companies, particularly ones that make use of AI, and 2) land, which has a fixed supply.

There are many ways to implement these two taxes, and many thoughts about what to do with them. Over a long period of time, perhaps most other taxes could be eliminated. What follows is an idea in the spirit of a conversation starter.

We could do something called the American Equity Fund. The American Equity Fund would be capitalized by taxing companies above a certain valuation 2.5% of their market value each year, payable in shares transferred to the fund, and by taxing 2.5% of the value of all privately-held land, payable in dollars.
 

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All citizens over 18 would get an annual distribution, in dollars and company shares, into their accounts. People would be entrusted to use the money however they needed or wanted—for better education, healthcare, housing, starting a company, whatever. Rising costs in government-funded industries would face real pressure as more people chose their own services in a competitive marketplace.

As long as the country keeps doing better, every citizen would get more money from the Fund every year (on average; there will still be economic cycles). Every citizen would therefore increasingly partake of the freedoms, powers, autonomies, and opportunities that come with economic self-determination. Poverty would be greatly reduced and many more people would have a shot at the life they want.

A tax payable in company shares will align incentives between companies, investors, and citizens, whereas a tax on profits does not–incentives are superpowers, and this is a critical difference. Corporate profits can be disguised or deferred or offshored, and are often disconnected from share price. But everyone who owns a share in Amazon wants the share price to rise. As people’s individual assets rise in tandem with the country’s, they have a literal stake in seeing their country do well.

Henry George, an American political economist, proposed the idea of a land-value tax in the late 1800s. The concept is widely supported by economists. The value of land appreciates because of the work society does around it: the network effects of the companies operating around a piece of land, the public transportation that makes it accessible, and the nearby restaurants, coffeeshops, and access to nature that makes it desirable. Because the landowner didn’t do all that work, it’s fair for that value to be shared with the larger society that did.

If everyone owns a slice of American value creation, everyone will want America to do better: collective equity in innovation and in the success of the country will align our incentives. The new social contract will be a floor for everyone in exchange for a ceiling for no one, and a shared belief that technology can and must deliver a virtuous circle of societal wealth. (We will continue to need strong leadership from our government to make sure that the desire for stock prices to go up remains balanced with protecting the environment, human rights, etc.)

In a world where everyone benefits from capitalism as an owner, the collective focus will be on making the world “more good” instead of “less bad.” These approaches are more different than they seem, and society does much better when it focuses on the former. Simply put, more good means optimizing for making the pie as large as possible, and less bad means dividing the pie up as fairly as possible. Both can increase people’s standard of living once, but continuous growth only happens when the pie grows.

Part 4

Implementation and Troubleshooting​


The amount of wealth available to capitalize the American Equity Fund would be significant. There is about $50 trillion worth of value, as measured by market capitalization, in US companies alone. Assume that, as it has on average over the past century, this will at least double over the next decade.

There is also about $30 trillion worth of privately-held land in the US (not counting improvements on top of the land). Assume that this value will roughly double, too, over the next decade–this is somewhat faster than the historical rate, but as the world really starts to understand the shifts AI will cause, the value of land, as one of the few truly finite assets, should increase at a faster rate.

Of course, if we increase the tax burden on holding land, its value will diminish relative to other investment assets, which is a good thing for society because it makes a fundamental resource more accessible and encourages investment instead of speculation. The value of companies will diminish in the short-term, too, though they will continue to perform quite well over time.

It’s a reasonable assumption that such a tax causes a drop in value of land and corporate assets of 15% (which only will take a few years to recover!).

Under the above set of assumptions (current values, future growth, and the reduction in value from the new tax), a decade from now each of the 250 million adults in America would get about $13,500 every year. That dividend could be much higher if AI accelerates growth, but even if it’s not, $13,500 will have much greater purchasing power than it does now because technology will have greatly reduced the cost of goods and services. And that effective purchasing power will go up dramatically every year.

It would be easiest for companies to pay the tax each year by issuing new shares representing 2.5% of their value. There would obviously be an incentive for companies to escape the American Equity Fund tax by off-shoring themselves, but a simple test involving a percentage of revenue derived from America could address this concern. A larger problem with this idea is the incentive for companies to return value to shareholders instead of reinvesting it in growth.

If we tax only public companies, there would also be an incentive for companies to stay private. For private companies that have annual revenue in excess of $1 billion, we could let their tax in equity accrue for a certain (limited) number of years until they go public. If they remain private for a long time, we could let them settle the tax in cash.

We’d need to design the system to prevent people from consistently voting themselves more money. A constitutional amendment delineating the allowable ranges of the tax would be a strong safeguard. It is important that the tax not be so large that it stifles growth–for example, the tax on companies must be much smaller than their average growth rate.

We’d also need a robust system for quantifying the actual value of land. One way would be with a corps of powerful federal assessors. Another would be to let local governments do the assessing, as they now do to determine property taxes. They would continue to receive local taxes using the same assessed value. However, if a certain percentage of sales in a jurisdiction in any given year falls too far above or below the local government’s estimate of the property’s values, then all the other properties in their jurisdiction would be reassessed up or down.

The theoretically optimal system would be to tax the value of the land only, and not the improvements built on top of it. In practice, this value may turn out to be too difficult to assess, so we may need to tax the value of the land and the improvements on it (at a lower rate, as the combined value would be higher).

Finally, we couldn’t let people borrow against, sell, or otherwise pledge their future Fund distributions, or we won’t really solve the problem of fairly distributing wealth over time. The government can simply make such transactions unenforceable.

Part 5

Shifting to the New System​


A great future isn’t complicated: we need technology to create more wealth, and policy to fairly distribute it. Everything necessary will be cheap, and everyone will have enough money to be able to afford it. As this system will be enormously popular, policymakers who embrace it early will be rewarded: they will themselves become enormously popular.

In the Great Depression, Franklin Roosevelt was able to enact a huge social safety net that no one would have thought possible five years earlier. We are in a similar moment now. So a movement that is both pro-business and pro-people will unite a remarkably broad constituency.

A politically feasible way to launch the American Equity Fund, and one that would reduce the transitional shock, would be with legislation that transitions us gradually to the 2.5% rates. The full 2.5% rate would only take hold once GDP increases by 50% from the time the law is passed. Starting with small distributions soon will be both motivating and helpful in getting people comfortable with a new future. Achieving 50% GDP growth sounds like it would take a long time (it took 13 years for the economy to grow 50% to its 2019 level). But once AI starts to arrive, growth will be extremely rapid. Down the line, we will probably be able to reduce a lot of other taxes as we tax these two fundamental asset classes.

The changes coming are unstoppable. If we embrace them and plan for them, we can use them to create a much fairer, happier, and more prosperous society. The future can be almost unimaginably great.

Thanks to Steven Adler, Daniela Amodei, Adam Baybutt, Chris Beiser, Jack Clark, Ryan Cohen, Tyler Cowen, Matt Danzeisen, Steve Dowling, Tad Friend, Lachy Groom, Chris Hallacy, Reid Hoffman, Ingmar Kanitscheider, Oleg Klimov, Matt Knight, Aris Konstantinidis, Andrew Kortina, Matt Krisiloff, Scott Krisiloff, John Luttig, Erik Madsen, Preston McAfee, Luke Miles, Arvind Neelakantan, David Oates, Cullen O’Keefe, Alethea Power, Raul Puri, Ilya Sutskever, Luke Walsh, Caleb Watney, and Wojchiech Zaremba for reviewing drafts of this, and to Gregory Koberger for designing it.
 

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1/11
@burkov
- Theranos: In a few months, our machine that does 3 tests will be able to do 250 tests.
- Tesla: Next year, our cars will drive 100% without a driver.
- Tesla: Our humanoid robots will soon live with you.
- OpenAI: We will achieve AGI in several thousand days.
- Anthropic: Our LLM that uses computers isn’t perfect yet but will be in a few months.

Why would all of them lie, and why would influencers amplify their lies?

It’s symbiosis. Tech companies lie because lies bring in billions of dollars—billions with a 'b'. Who wouldn’t like that? Influencers do it for likes. If you repeat these lies, you get five times more likes compared to calling out the bullshyt. So, influencers are like the remora fish that live in a symbiotic relationship with sharks, cleaning their teeth.



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2/11
@michael_kove
Theranos lied with absolutely nothing behind their claim.

At least other companies shipped something tangible even if not fully functional



3/11
@burkov
They learned from Theranos' mistake.



4/11
@Hochmeister
Setting ambitious goals, even if you know they are unlikely to be met is not a lie. Saying you achieved the thing when you have not is the lie which is what Theranos did.



5/11
@burkov
Lend me $100. My ambitious goal is to pay you $110 back. If I only pay you $5, you should understand, it wasn't a lie. Just my ambitions were too ambitious.



6/11
@FeatureCrewPod
I mean its not fraud, its an early demo

[Quoted tweet]
New #AI Agent from @AnthropicAI can now...
📧 Delete emails
🗂️ Manage files
🎨 Try to draw
Watch the full video:


https://video.twimg.com/amplify_video/1848941581199400960/vid/avc1/1920x1080/NGOul_PPaOzxRNk9.mp4

7/11
@burkov
They said that in several months it will become perfect. It's a lie.



8/11
@ICannot_Enough
Are you proud of influencing /search?q=#TSLA investors to sell in May of 2020 (at a split-adjusted ~$55 per share), talking them out of making a 4x or better profit?



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9/11
@62fidla
I like that: "influencers are like the remora fish that live in a symbiotic relationship with sharks, cleaning their teeth."



10/11
@sudobashman
I think being optimistic is fine, but it has to be grounded in science, not false optimism. Quite often you get a Eureka moment, but then lots of hard slog and dev to get the thing into a shape that works/is functional. Lying is pretending you've had the Eureka moment when you haven't. In that scenario, saying you have/it'll be fine is the same as lying.



11/11
@Terje4Liberty
This comparison is utterly ridiculous. Sure, Theranos made big promises regarding its future capabilities just like others do. However, it also outright lied about its current technology. The core product, a blood-testing device called the "Edison," was described as being able to run a wide array of medical tests using just a few drops of blood. However, the technology never worked. And they engaged in deceit to make people think it did.

Theranos CEO Elizabeth Holmes was charged with wire fraud and conspiracy, found guilty on four counts and sentenced to 11 years and 3 months in prison.




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