Spectrum’s Top AI Stories of 2023

2023 might properly go down in historical past as probably the most wild and dramatic years within the historical past of artificial intelligence. People had been nonetheless struggling to know the facility of OpenAI’s ChatGPT, which had been launched in late 2022, when the corporate launched its latest giant language mannequin, GPT-4, in March 2023 (LLMs are primarily the brains behind consumer-facing purposes).

All by way of the spring of 2023, necessary and credible individuals freaked out in regards to the doable damaging penalties—starting from considerably troubling to existentially dangerous—of ever-improving AI. First got here an open letter calling for a pause on the event of superior fashions, then a assertion about existential danger, the primary worldwide summit on AI security, and landmark rules within the type of a U.S. government order and the E.U. AI Act.

Here are Spectrum’s high 10 articles of 2023 about AI, based on how a lot time readers spent with them. Take a glance to get the flavour of AI in 2023, a 12 months which will properly go down in historical past… except 2024 is even crazier.

10. AI Art Generators Can Be Fooled Into Making NSFW Images:

Pai-Shih Lee/Getty Images

With text-to-image turbines like Dall-E 2 and Stable Diffusion, customers kind a immediate describing the picture they’d like to supply, and the mannequin does the remainder. And whereas they’ve safeguards to maintain customers from producing violent, pornographic, and in any other case unacceptable photos, each AI researchers and hackers have taken enjoyment of determining easy methods to circumvent such safeguards. For white hats and black hats, jailbreaking is the brand new passion.

9. OpenAI’s Moonshot: Solving the AI Alignment Problem:

Daniel Zender

This Q&A with OpenAI’s Jan Leike delves into the AI alignment drawback. That’s the priority that we might construct superintelligent AI techniques whose targets should not aligned with these of people, probably resulting in the extinction of our species. It’s legitimately an necessary challenge, and OpenAI is devoting severe assets to discovering methods to empirically analysis an issue that doesn’t but exist (as a result of superintelligent AI techniques don’t but exist).

8. The Secret to Nvidia’s Success:

I-Hwa Cheng/Bloomberg/Getty Images

Nvidia had a terrific 12 months as its AI-accelerating GPU, the H-100, turned arguably the most popular piece of {hardware} in tech. The firm’s chief scientist, Bill Dally, mirrored at a convention on the 4 substances that launched Nvidia into the stratosphere. “Moore’s Law was a surprisingly small part of Nvidia’s magic and new number formats a very large part,” writes IEEE Spectrum senior editor Sam Moore.

7. ChatGPT’s Hallucinations Could Keep It from Succeeding:

Zuma/Alamy

One challenge that has bedeviled LLMs is their behavior of constructing issues up—unpredictably spouting lies in a most assured tone. This behavior is a specific drawback when individuals attempt to use it for issues that actually matter, like writing authorized briefs. OpenAI believes it’s a solvable drawback, however some outdoors consultants, like Meta AI’s Yann LeCun, disagree.

6. Ten Essential Insights into the State of AI in 2023, in Graphs:

It’s an inventory inside an inventory! Every 12 months, Spectrum editors unpack the large AI Index issued by the Stanford Institute for Human-Centered Artificial Intelligence, distilling the report down right into a handful of graphs that talk to crucial tendencies. In 2023, highlights included the prices and vitality necessities of coaching giant fashions, and business’s dominance over academia relating to recruiting Ph.D.s and constructing fashions.

5. The Creepy New Digital Afterlife Industry:

Harry Campbell

Here’s an excerpt from a wonderful guide referred to as We, the Data, by Wendy H. Wong. The excerpt takes an extended take a look at the companies which might be popping up as a part of the brand new digital afterlife business: Some firms provide to ship out messages in your behalf after your demise, others allow you to document tales that others can later play again by asking questions. And there have already been just a few examples of individuals constructing digital replicas of deceased family members based mostly on the info they left behind.

4. The AI Apocalypse: A Scorecard:

IEEE Spectrum

This undertaking happened as Spectrum editors mentioned how shocking it’s that actually good AI practitioners—individuals who have labored within the subject for many years—can have such very opposing views on two necessary questions. Namely, are right now’s LLMs an indication that AI will quickly obtain superhuman intelligence, and would such superintelligent AI techniques spell doom for Homo sapiens. To assist readers perceive the vary of opinions, we put collectively a scorecard.

3. 200-Year-Old Math Opens Up AI’s Mysterious Black Box:

P. Hassanzadeh/Rice University

The neural networks that energy a lot of AI right now are famously black bins; researchers give them the coaching information and see the outcomes, however don’t have a lot perception into what occurs in between. One set of researchers who work on fluid dynamics determined to make use of Fourier evaluation, a math approach used to determine patterns that’s been round for roughly 200 years, to review neural nets educated to foretell turbulence.

2. How Duolingo’s AI Learns What You Need to Learn:

Eddie Guy

This article is considered one of Spectrum‘s signature deep dives, a feature article written by the experts who are building the technology. In this case, it’s the AI staff behind Duolingo, the language-learning app. They clarify how they developed Birdbrain, an AI system that pulls on each instructional psychology and machine studying to current customers with classes which might be at simply the best degree of issue to maintain them engaged.

1. Just Calm Down About GPT-4 Already:

Rodney Brooks: Christopher Michel/Wikipedia; Background: Ruby Chen/OpenAI

Spectrum readers have a contrarian streak, and thus fairly loved this Q&A with Rodney Brooks, a self-described AI skeptic who has been working within the subject for many years. Rather than hailing GPT-4 as a step towards synthetic basic intelligence, Brooks drew consideration to the LLM’s issue in generalizing from one process to a different. “What the massive language fashions are good at is saying what a solution ought to sound like, which is completely different from what a solution ought to be,“ he stated.