The Coming Wave: AI, Power, and Our Future

by Mustafa Suleyman

the average American reads a book for about fifteen minutes per day,

Alibaba has already developed a model that claims to have ten trillion parameters.

floating-point operation

(FLOP)

“the scaling hypothesis,” which predicts that the main driver of performance is, quite simply, to go big and keep going bigger.

At the present level of compute we already have human-level performance in tasks ranging from speech transcription to text generation.

AI will keep getting radically better at everything, and so far there seems no obvious upper limit on what’s possible.

AI increasingly does more with less.

EleutherAI,

a grassroots coalition of independent researchers,

nimble creators working with efficient systems, curated data sets, and quick iterations can already quickly rival the most well-resourced developers.

A fully open-source model called Stable Diffusion lets anyone produce bespoke and ultrarealistic images, for free, on a laptop.

In 2022, OpenAI and Microsoft unveiled a new tool called Copilot,

of course all programs in the future will ultimately be written by AIs, with humans relegated to, at best, a supervisory role.”

screeds

rambling

The potential for harm, abuse, and misinformation is real. But the positive news is that many of these issues are being improved with larger and more powerful models.

the future of computing was conversational.

LaMDA,

short for Language Model for Dialogue Applications. LaMDA

Blake Lemoine,

AI had reached a point where it could convince otherwise intelligent people—indeed, someone with a real understanding of how it actually worked—that it was conscious.

blasé

present-day AI systems have many limitations: they can’t transfer knowledge from one domain to another, provide quality explanations of their decision-making process,

Significant challenges with real-world applications linger, including material questions of bias and fairness, reproducibility, security vulnerabilities, and legal liability. Urgent ethical gaps and unsolved safety questions cannot be ignored.

recursively self-improving AI would lead to an “intelligence explosion” known as the Singularity.

One particularly important dimension is in the ability to take actions. We don’t just care about what a machine can say; we also care about what it can do.

What we would really like to know is, can I give an AI an ambiguous, open-ended, complex goal that requires interpretation, judgment, creativity, decision-making, and acting across multiple domains, over an extended time period, and then see the AI accomplish that goal?

passing a Modern Turing Test would involve something like the following: an AI being able to successfully act on the instruction “Go make $1 million on Amazon in a...

I think it will be done with a few minor human interventions within the next year, and probably fully autonomously within three to five years.

The challenge is in advancing what AI developers call hierarchical planning, stitching multiple goals and subgoals and capabilities into a seamless process toward a singular end.

“artificial capable intelligence” (ACI), the point at which AI can achieve complex goals and tasks with minimal oversight.

glimmers

ACI represents the next stage of AI’s evolution.

interactive—operating in real time, with real users. It would augment these abilities with a reliable memory so that it could be consistent over extended timescales and could draw on other sources of data, including, for example, databases of knowledge, products, or supply-chain components belonging to third parties. Such a system would use these resources to weave together sequences of actions into long-term plans in pursuit of complex, open-ended goals, like setting up and running an Amazon Marketplace store.

a genuinely capable AI, an ACI.

vast array of conceivable goals: planning and running your vacation, designing and building more efficient solar panels, helping win an election.

more dramatic leaps forward, including breakthroughs toward AI that can imagine, reason, plan, and exhibit common sense.

It’s not just a tool or platform but a transformative meta-technology,

Biology’s mysteries began to unravel, and biology itself became an engineering tool.

the coming decades will be defined by a convergence of biology and engineering.

At the center of this wave sits the realization that DNA is information, a biologically evolved encoding and storage system.

Rosalind Franklin

Maurice Wilkins,

James ...

Francis...

Stanley N. Cohen

Herbert W. Boyer

found ways of transplanting genetic material from one org...

This research led Boyer to found one of the world’s first biotech companies, Genentech, in 1976. Its mission was to manipulate the genes of microorganisms to produce medicines and treatments, and within a year it had developed a proof of concept, using engineered E. coli bacteria to produce the hormone somatostatin.