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AI Eye: Real uses for AI in crypto, Google’s GPT-4 rival, AI edge for bad employees
How Maker, The Sandbox and Near are using AI in crypto, plus terrible workers benefit most from AI and Google’s GPT-4 rival nears release.
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How Maker, The Sandbox and Near are using AI in crypto, plus terrible workers benefit most from AI and Google’s GPT-4 rival nears release.
AI and crypto isnt just a buzz phrase
AI Eye has been out and about at Korean Blockchain Week and Token2049 in Singapore over the past fortnight, trying to find out how crypto project leaders plan to use AI.
Probably the most well-known is Maker founder Rune Christensen, who essentially plans to relaunch his decade-old project as a bunch of sub-DAOs employing AI governance.
“People misunderstand what we mean with AI governance, right? We’re not talking about AI running a DAO,” he says, adding the AI wont be enforcing any rules. The AI cannot do that because it’s unreliable.” Instead the project is working on using AI for coordination and communication as an Atlas to the entire project, as theyre calling it.
“Having that sort of central repository of data just makes it actually realistic to have hundreds of thousands of people from different backgrounds and different levels of understanding meaningfully collaborate and interact because they’ve got this shared language.”
Near founder Illia Polosukhin may be better known in AI circles as his project began life as an AI startup before pivoting to blockchain. Polosukhin was one of the authors of the seminal 2017 Transformer paper (“Attention Is All You Need”) that laid the groundwork for the explosion of generative AI like ChatGPT over the past year.
Polosukhin has too many ideas about legitimate AI use cases in crypto to detail here, but one hes very keen on is using blockchain to prove the provenance of content so that users can distinguish between genuine content and AI-generated bullshit. Such a system would encompass provenance and reputation using cryptography.
“So cryptography becomes like an instrument to ensure consistency and traceability. And then you need reputation around this cryptography, which is on-chain accounts and record keeping to actually ensure that [X] posted this and [X] is working for Cointelegraph right now.”
Sebastien Borget from The Sandbox says the platform has been using AI for content moderation over the past year. “In-game conversation in any language is actually being filtered, so there is no more toxicity,” he explains. The project is also examining its use for music and avatar generation, as well as for more general user-generated content for world-building.
Meanwhile, Framework Ventures founder Vance Spencer outlined four main use cases for AI, with the most interesting by far training up AI models and then selling them as tokens on-chain. As luck would have it, Frameworks has invested in a game called AI Arena, in which players train AI models to compete in the game.
Keep an eye out for in-depth Magazine features outlining their thoughts in more detail.
AI is for communists?
Speaking of AI and crypto, are they pulling in opposite directions? Dynamo Daos Patrick Scott dug up PayPal founder Peter Thiels thoughts on AI and crypto in his forward to the re-release of the 1997 non-fiction book The Sovereign Individual, which predicted cryptocurrency, among other things. In it, Thiel argues AI is a technology of control, while crypto is one of liberation.
“AI could theoretically make it possible to centrally control an entire economy. It is no coincidence that AI is the favorite technology of the Communist Party of China. Strong cryptography, at the other pole, holds out the prospect of a decentralized and individualized world. If AI is communist, crypto is libertarian.”
From Peter Thiel’s new 2020 preface to The Sovereign Individual. pic.twitter.com/cWzfgyUqfY
Patrick Scott | Dynamo DeFi (@Dynamo_Patrick) September 17, 2023
Roblox lets users build with AI
Roblox has unveiled a new feature called Assistant, which will let users build virtual assets and write code using generative AI. In the demo, users write something like “make a game set in ancient ruins” and “add some trees,” and the AI does the rest. It’s still being developed and will be released at the end of this year or early next year. The plan is for Assistant to one day generate sophisticated gameplay or make 3D models from scratch.
Terrible workers benefit most from AI
The worst workers at your place of employment are likely to benefit the most from using AI tools, according to a new study by Boston Consulting Group. The output of below-average workers improved by 43% when using AI, while the output of above-average workers improved by just 17%.
Interestingly, workers who used AI for things beyond its current abilities performed 20% worse because the AI would present them with plausible but wrong responses.
Google Gemini gears up for release
Googles GPT-4 competitor is nearing release, with The Information reporting that a small group of companies has been given early access to Gemini. For those who came in late, Google was seen leading the AI race right up until OpenAI dumped ChatGPT on the market in November last year (arguably before it was ready) and leaped ahead.
Google hopes Gemini can best GPT-4 by offering not just text generation capabilities but also image generation, enabling the creation of contextual images (rumors suggest its being trained on YouTube content, among other data). There are plans in future for features like using it to control software with your voice or to analyze charts. Highlighting how important Gemini is, Google co-founder Sergey Brin is said to be playing an instrumental role in the evaluation and training of the models.
AI expert Brian Roemmele says hes been testing a version of Gemini and finds it “equivalent to ChatGPT-4 but with newly up to the second knowledge base. This saves it from some hallucinations.”
Google CEO Sundar Pichai told Wired this week he has no regrets about not launching its chatbot early to beat ChatGPT because the tech “needed to mature a bit more before we put it in our products.”
“It’s not fully clear to me that it might have worked out as well,” Pichai said. “The fact is, we could do more after people had seen how it works. It really won’t matter in the next five to 10 years.”
AI meets 15-minute cities
Researchers at Tsinghua University in China have built an AI system that plans out cities in line with current thinking about walkable 15-minute cities that have lots of green space (please direct conspiracy theories about the topic to X).
The researchers found the AI was better at tedious computation and repetitive tasks and was able to complete in seconds what human planners required 50 to 100 minutes to work through. Overall, they determined it was able to improve on human designs by 50% when assessed on access to services, green spaces and traffic levels.
The headline figure is a bit misleading, though, as the finished plans only increased access to basic services by 12% and to parks by 5%. In a blind judging process, 100 urban planners preferred some of the AI designs by a clear margin but expressed no preference for other designs. The researchers envisage their AI working as an assistant doing the boring stuff while humans focus on more challenging and creative aspects.
Stephen Fry is cloned
Blackadder and QI star and much-loved British comedy institution Stephen Fry says he has become a victim of AI voice cloning.
On September 14, Fry played a clip from a historical documentary he apparently narrated at the CogX Festival in London last week but revealed the voice wasnt him at all. I said not one word of that it was a machine, he said. They used my reading of the seven volumes of the Harry Potter books, and from that dataset an AI of my voice was created, and it made that new narration.
Training AI to rip off the work of actors and repurpose them elsewhere without payment is one of the key issues in the current actors and writers strike in Hollywood. Fry said the incident was just the tip of the iceberg, and AI will advance at a faster rate than any technology we have ever seen. One thing we can all agree on: its a fucking weird time to be alive.
How not to cheat using ChatGPT
The sort of academics drawn to cheating using ChatGPT appear to be the sort of people who make dumb mistakes giving that fact away. A paper published in the journal Physica Scripta was retracted after computer scientist Guillaume Cabanac noticed the regenerate response in the text, indicating it had been copied directly from ChatGPT.
Cabanac has helped uncover hundreds of AI-generated academic manuscripts since 2015, including a paper in the August edition of Resources Policy, which contained the tell-tale line: Please note that as an AI language model, I am unable to
All Killer No Filler AI News
Meta is also working on a new model to compete with GPT-4 that it aims to launch in 2024, according to The Wall Street Journal. It is intended to be many times more powerful than its existing Llama 2.
Microsoft has open-sourced a novel protein-generating AI called EvoDiff. It works like Stable Diffusion and Dall-E2, but instead of generating images, it designs proteins that can be used for specific medical purposes. This is expected to lead to new classes of drugs and therapies.
Defense contractor Palantir, along with Cohere, IBM, Nvidia, Salesforce, Scale AI and Stability, have signed up to the White Houses somewhat vague plans for responsible AI development. The administration is also developing an executive order on AI and plans to introduce bipartisan legislation.
Sixty U.S. senators attended a private briefing recently about the risks of AI from 20 Silicon Valley CEOs and wonks, including Sam Altman, Mark Zuckerberg and Bill Gates. Elon Musk told reporters afterward that the meeting “may go down in history as very important to the future of civilization.”
ChatGPT traffic has fallen for three months in a row, by roughly 10% in both June and July and a further 3.2% drop in August. The amount of time users spend on the site fell from 8.7 minutes on average in March to seven minutes last month.
Finnish prisoners are being paid $1.67 to help train AI models for a startup called Metroc. The AI is learning how to determine when construction projects are hiring.
The U.S. is way out in front of the AI race, with 4,643 startups and $249 billion of investment since 2013, which is 1.9 times more startups than China and Europe combined.
Video of the week
Writer and storyteller Jon Finger tried out the HeyGen video app, which is able to not only translate his words but also clone his voice AND sync up his lip movements to the translated text.
Testing out @HeyGen_Official translation on French and German. I dont speak either language so let me know if it sounds natural if you do.
I hope if you pay you can turn off the color correction.
It didnt work on my phone so I had to upload on my pc.https://t.co/FMJp9sJEBI pic.twitter.com/iF5eONAQ3cJon Finger (@mrjonfinger) September 11, 2023
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Homes listed for sale in early June sell for $7,700 more
New Zillow research suggests the spring home shopping season may see a second wave this summer if mortgage rates fall
The post Homes listed for sale in…
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- A Zillow analysis of 2023 home sales finds homes listed in the first two weeks of June sold for 2.3% more.
- The best time to list a home for sale is a month later than it was in 2019, likely driven by mortgage rates.
- The best time to list can be as early as the second half of February in San Francisco, and as late as the first half of July in New York and Philadelphia.
Spring home sellers looking to maximize their sale price may want to wait it out and list their home for sale in the first half of June. A new Zillow® analysis of 2023 sales found that homes listed in the first two weeks of June sold for 2.3% more, a $7,700 boost on a typical U.S. home.
The best time to list consistently had been early May in the years leading up to the pandemic. The shift to June suggests mortgage rates are strongly influencing demand on top of the usual seasonality that brings buyers to the market in the spring. This home-shopping season is poised to follow a similar pattern as that in 2023, with the potential for a second wave if the Federal Reserve lowers interest rates midyear or later.
The 2.3% sale price premium registered last June followed the first spring in more than 15 years with mortgage rates over 6% on a 30-year fixed-rate loan. The high rates put home buyers on the back foot, and as rates continued upward through May, they were still reassessing and less likely to bid boldly. In June, however, rates pulled back a little from 6.79% to 6.67%, which likely presented an opportunity for determined buyers heading into summer. More buyers understood their market position and could afford to transact, boosting competition and sale prices.
The old logic was that sellers could earn a premium by listing in late spring, when search activity hit its peak. Now, with persistently low inventory, mortgage rate fluctuations make their own seasonality. First-time home buyers who are on the edge of qualifying for a home loan may dip in and out of the market, depending on what’s happening with rates. It is almost certain the Federal Reserve will push back any interest-rate cuts to mid-2024 at the earliest. If mortgage rates follow, that could bring another surge of buyers later this year.
Mortgage rates have been impacting affordability and sale prices since they began rising rapidly two years ago. In 2022, sellers nationwide saw the highest sale premium when they listed their home in late March, right before rates barreled past 5% and continued climbing.
Zillow’s research finds the best time to list can vary widely by metropolitan area. In 2023, it was as early as the second half of February in San Francisco, and as late as the first half of July in New York. Thirty of the top 35 largest metro areas saw for-sale listings command the highest sale prices between May and early July last year.
Zillow also found a wide range in the sale price premiums associated with homes listed during those peak periods. At the hottest time of the year in San Jose, homes sold for 5.5% more, a $88,000 boost on a typical home. Meanwhile, homes in San Antonio sold for 1.9% more during that same time period.
| Metropolitan Area | Best Time to List | Price Premium | Dollar Boost |
| United States | First half of June | 2.3% | $7,700 |
| New York, NY | First half of July | 2.4% | $15,500 |
| Los Angeles, CA | First half of May | 4.1% | $39,300 |
| Chicago, IL | First half of June | 2.8% | $8,800 |
| Dallas, TX | First half of June | 2.5% | $9,200 |
| Houston, TX | Second half of April | 2.0% | $6,200 |
| Washington, DC | Second half of June | 2.2% | $12,700 |
| Philadelphia, PA | First half of July | 2.4% | $8,200 |
| Miami, FL | First half of June | 2.3% | $12,900 |
| Atlanta, GA | Second half of June | 2.3% | $8,700 |
| Boston, MA | Second half of May | 3.5% | $23,600 |
| Phoenix, AZ | First half of June | 3.2% | $14,700 |
| San Francisco, CA | Second half of February | 4.2% | $50,300 |
| Riverside, CA | First half of May | 2.7% | $15,600 |
| Detroit, MI | First half of July | 3.3% | $7,900 |
| Seattle, WA | First half of June | 4.3% | $31,500 |
| Minneapolis, MN | Second half of May | 3.7% | $13,400 |
| San Diego, CA | Second half of April | 3.1% | $29,600 |
| Tampa, FL | Second half of June | 2.1% | $8,000 |
| Denver, CO | Second half of May | 2.9% | $16,900 |
| Baltimore, MD | First half of July | 2.2% | $8,200 |
| St. Louis, MO | First half of June | 2.9% | $7,000 |
| Orlando, FL | First half of June | 2.2% | $8,700 |
| Charlotte, NC | Second half of May | 3.0% | $11,000 |
| San Antonio, TX | First half of June | 1.9% | $5,400 |
| Portland, OR | Second half of April | 2.6% | $14,300 |
| Sacramento, CA | First half of June | 3.2% | $17,900 |
| Pittsburgh, PA | Second half of June | 2.3% | $4,700 |
| Cincinnati, OH | Second half of April | 2.7% | $7,500 |
| Austin, TX | Second half of May | 2.8% | $12,600 |
| Las Vegas, NV | First half of June | 3.4% | $14,600 |
| Kansas City, MO | Second half of May | 2.5% | $7,300 |
| Columbus, OH | Second half of June | 3.3% | $10,400 |
| Indianapolis, IN | First half of July | 3.0% | $8,100 |
| Cleveland, OH | First half of July | 3.4% | $7,400 |
| San Jose, CA | First half of June | 5.5% | $88,400 |
The post Homes listed for sale in early June sell for $7,700 more appeared first on Zillow Research.
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February Employment Situation
By Paul Gomme and Peter Rupert The establishment data from the BLS showed a 275,000 increase in payroll employment for February, outpacing the 230,000…
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By Paul Gomme and Peter Rupert
The establishment data from the BLS showed a 275,000 increase in payroll employment for February, outpacing the 230,000 average over the previous 12 months. The payroll data for January and December were revised down by a total of 167,000. The private sector added 223,000 new jobs, the largest gain since May of last year.
Temporary help services employment continues a steep decline after a sharp post-pandemic rise.
Average hours of work increased from 34.2 to 34.3. The increase, along with the 223,000 private employment increase led to a hefty increase in total hours of 5.6% at an annualized rate, also the largest increase since May of last year.
The establishment report, once again, beat “expectations;” the WSJ survey of economists was 198,000. Other than the downward revisions, mentioned above, another bit of negative news was a smallish increase in wage growth, from $34.52 to $34.57.
The household survey shows that the labor force increased 150,000, a drop in employment of 184,000 and an increase in the number of unemployed persons of 334,000. The labor force participation rate held steady at 62.5, the employment to population ratio decreased from 60.2 to 60.1 and the unemployment rate increased from 3.66 to 3.86. Remember that the unemployment rate is the number of unemployed relative to the labor force (the number employed plus the number unemployed). Consequently, the unemployment rate can go up if the number of unemployed rises holding fixed the labor force, or if the labor force shrinks holding the number unemployed unchanged. An increase in the unemployment rate is not necessarily a bad thing: it may reflect a strong labor market drawing “marginally attached” individuals from outside the labor force. Indeed, there was a 96,000 decline in those workers.
Earlier in the week, the BLS announced JOLTS (Job Openings and Labor Turnover Survey) data for January. There isn’t much to report here as the job openings changed little at 8.9 million, the number of hires and total separations were little changed at 5.7 million and 5.3 million, respectively.
As has been the case for the last couple of years, the number of job openings remains higher than the number of unemployed persons.
Also earlier in the week the BLS announced that productivity increased 3.2% in the 4th quarter with output rising 3.5% and hours of work rising 0.3%.
The bottom line is that the labor market continues its surprisingly (to some) strong performance, once again proving stronger than many had expected. This strength makes it difficult to justify any interest rate cuts soon, particularly given the recent inflation spike.
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Mortgage rates fall as labor market normalizes
Jobless claims show an expanding economy. We will only be in a recession once jobless claims exceed 323,000 on a four-week moving average.
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Everyone was waiting to see if this week’s jobs report would send mortgage rates higher, which is what happened last month. Instead, the 10-year yield had a muted response after the headline number beat estimates, but we have negative job revisions from previous months. The Federal Reserve’s fear of wage growth spiraling out of control hasn’t materialized for over two years now and the unemployment rate ticked up to 3.9%. For now, we can say the labor market isn’t tight anymore, but it’s also not breaking.
The key labor data line in this expansion is the weekly jobless claims report. Jobless claims show an expanding economy that has not lost jobs yet. We will only be in a recession once jobless claims exceed 323,000 on a four-week moving average.
From the Fed: In the week ended March 2, initial claims for unemployment insurance benefits were flat, at 217,000. The four-week moving average declined slightly by 750, to 212,250
Below is an explanation of how we got here with the labor market, which all started during COVID-19.
1. I wrote the COVID-19 recovery model on April 7, 2020, and retired it on Dec. 9, 2020. By that time, the upfront recovery phase was done, and I needed to model out when we would get the jobs lost back.
2. Early in the labor market recovery, when we saw weaker job reports, I doubled and tripled down on my assertion that job openings would get to 10 million in this recovery. Job openings rose as high as to 12 million and are currently over 9 million. Even with the massive miss on a job report in May 2021, I didn’t waver.
Currently, the jobs openings, quit percentage and hires data are below pre-COVID-19 levels, which means the labor market isn’t as tight as it once was, and this is why the employment cost index has been slowing data to move along the quits percentage.
3. I wrote that we should get back all the jobs lost to COVID-19 by September of 2022. At the time this would be a speedy labor market recovery, and it happened on schedule, too
Total employment data
4. This is the key one for right now: If COVID-19 hadn’t happened, we would have between 157 million and 159 million jobs today, which would have been in line with the job growth rate in February 2020. Today, we are at 157,808,000. This is important because job growth should be cooling down now. We are more in line with where the labor market should be when averaging 140K-165K monthly. So for now, the fact that we aren’t trending between 140K-165K means we still have a bit more recovery kick left before we get down to those levels.
From BLS: Total nonfarm payroll employment rose by 275,000 in February, and the unemployment rate increased to 3.9 percent, the U.S. Bureau of Labor Statistics reported today. Job gains occurred in health care, in government, in food services and drinking places, in social assistance, and in transportation and warehousing.
Here are the jobs that were created and lost in the previous month:
In this jobs report, the unemployment rate for education levels looks like this:
- Less than a high school diploma: 6.1%
- High school graduate and no college: 4.2%
- Some college or associate degree: 3.1%
- Bachelor’s degree or higher: 2.2%
Today’s report has continued the trend of the labor data beating my expectations, only because I am looking for the jobs data to slow down to a level of 140K-165K, which hasn’t happened yet. I wouldn’t categorize the labor market as being tight anymore because of the quits ratio and the hires data in the job openings report. This also shows itself in the employment cost index as well. These are key data lines for the Fed and the reason we are going to see three rate cuts this year.
recession unemployment covid-19 fed federal reserve mortgage rates recession recovery unemployment
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