No 42: The value creation of Generative AI is here
No 42: The value creation of Generative AI is here
Rapid change is too gentle to describe the impact of generative AI is having today
Exploring the collision between the future of learning, work, and AI.
First, some numbers:
$10,000 - A ghostwriter for VC’s reveals he can get paid $5-10k per month for 10 tweets.
80% - GitHub’s Copilot AI can write up to 40% of the code for programmers and is heading up to 80% within five years, says GitHub CEO Thomas Dohmke.
10 million - Creator Boris Dayma of Craiyon AI estimates their image generator is making over 10 million images a day. Create your own at Craiyon.com.
What’s ahead for Generative AI - via Sequoia Capital
Generative AI is well on the way to becoming not just faster and cheaper, but better in some cases than what humans create by hand. Every industry that requires humans to create original work—from social media to gaming, advertising to architecture, coding to graphic design, product design to law, marketing to sales—is up for reinvention. Certain functions may be completely replaced by generative AI, while others are more likely to thrive from a tight iterative creative cycle between human and machine—but generative AI should unlock better, faster and cheaper creation across a wide range of end markets. The dream is that generative AI brings the marginal cost of creation and knowledge work down towards zero, generating vast labor productivity and economic value—and commensurate market cap.
The fields that generative AI addresses—knowledge work and creative work—comprise billions of workers. Generative AI can make these workers at least 10% more efficient and/or creative: they become not only faster and more efficient, but more capable than before. Therefore, Generative AI has the potential to generate trillions of dollars of economic value.
Read the full report at Sequoia Capital
Note: GPT-3 has a byline as one of the co-writers of this piece.
Microsoft’s GitHub Copilot AI is making rapid progress writing code for developers
In school, a common path is encouraging students to become coders. But today, AI is already writing code for many current developers.
“AI will transform all industries,” Hoffman told the members of the CNBC Technology Executive Council. “So everyone has to be thinking about it, not just in data science.”
The rapid advances being made by Copilot AI, the automated code writing tool from the GitHub open source subsidiary of Microsoft, were an example Hoffman, who is on the Microsoft board, directly cited as a signal that all firms better be prepared for AI in their world. Even if not making big investments today in AI, business leaders must understand the pace of improvement in artificial intelligence and the applications that are coming or they will be “sacrificing the future,” he said.
“100,000 developers took 35% of the coding suggestions from Copilot,” Hoffman said. “That’s a 35% increase in productivity, and off last year’s model. ... Across everything we are doing, we will have amplifying tools, it will get there over the next three to 10 years, a baseline for everything we are doing,” he added.
Copilot has already added another 5% to the 35% cited by Hoffman. GitHub CEO Thomas Dohmke recently told us that Copilot is now handling up to 40% of coding among programmers using the AI in the beta testing period over the past year. Put another way, for every 100 lines of code, 40 are being written by the AI, with total project time cut by up to 55%.
Read further on CNBC.com
In Pursuing Human-Level Intelligence, The AI Industry Risks Building What It Can’t Control
It’s admittedly a strange time to discuss whether AI can mirror human intelligence — and what weird things will happen along the way — because much of what AI does today is elementary. The shortcomings and challenges of current systems are easy to point out, and many in the field prefer not to engage with longer-term questions (like whether AI can become sentient) since they believe their energy is better spent on immediate problems. Shorttermists and longtermists are two separate factions in the AI world.
TL;DR Conclusion
To think differently than how J. Robert Oppenheimer, who led work on the atomic bomb, put it. “When you see something that is technically sweet,” he said. “You go ahead and do it and you argue about what to do about it only after you have had your technical success.”
Perhaps more thought this time would lead to a better outcome.
Read the full article via Big Technology newsletter.
Till next time…
We get one life. One. And then that’s it. There’s nothing after. Who wants to spend it [climbing] a ladder?
— Antoine Wilson, Mouth to Mouth