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Researchers are closer to solving how AI 'thinks'

ALSO: Nvidia's big day

Read time: under 4 minutes

Welcome back, Superhuman

In February, Nvidia added $277 billion to its value in a single day, setting a new record. Onlookers wondered whether that momentum might fizzle out. But Wednesday’s results did just the opposite, making investors even more excited about AI’s future.

Today’s Insights

  • Nvidia’s long-awaited financial results are in

  • Prompt: Coding Skills, Enhanced

  • Shining a light on AI’s ‘black box’

  • 5 new AI tools to boost your productivity

  • Everything else you should know today

  • AI-Generated Images: 1940s ads for modern-day brands

NEXT IN AI

Nvidia’s earnings report shakes up the AI world — and beyond

Source: Getty Images

Nvidia had a lot to live up to. It’s practically carrying the AI world on its shoulders with the state-of-the-art chips that power most of today’s big models. At its earnings report Wednesday, the company not only surpassed forecaster’s predictions but posted a quarterly revenue of $26 billion — up 262% from a year ago.

Some context: In early 2023, most people thought of Nvidia as just another chip developer. That all changed when tech companies started to release the first ChatGPT rivals later that year. Nvidia’s graphics processing units (GPUs) happened to be especially good at training AI models, and demand shot through the roof. Nvidia never looked back: The company now has a market capitalization of over $2.3 trillion, putting it behind only Microsoft and Apple.

Why it’s important: Nvidia now has the power to literally move markets. It’s estimated that the California-based firm was responsible for 2.5 points of the S&P 500’s 10.3% growth this past year. As Bloomberg recently put it: “One company’s results have come to have the kind of impact normally reserved for macro events like monetary policy shifts or financial crises.”

Nvidia’s financial situation shapes how the rest of the AI market looks, too. Will investors continue funneling funds into AI startups, allowing them to push the envelope with bigger and better models? Or will Wall Street hold off, forcing tech companies to make do with tighter budgets? Nvidia’s strong performance might show the industry that there’s still room to grow.

Competitors are catching up, slowly but surely: Longtime rivals like AMD and Intel, along with newcomers like Groq and Cerebras, are developing their own GPUs — although most won’t be ready for at least a few years. Still, Nvidia might just be too quick for them. According to Barron’s, the company has managed to double its architecture’s processing power every six months — proving its success is based on more than hype alone.

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PROMPT OF THE DAY

Develop your coding skills

Prompt: Take this [Java or other language] code and rewrite it into the [C++ or any desired Language], ensuring that functionality remains consistent.

Source: Great AI Prompts

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AI & THE MIND

Inside the mind of an AI

Source: Anthropic

We’re still trying to understand the inner workings of our own brains. But studying how AI “thinks” is like peering into the mind of an alien species. AI developers know their models work, but ask them how they work, and you’ll get only educated guesses.

Researchers at Anthropic believe they’re one step closer to finding a definitive answer: They set out to solve a mystery that has puzzled computer scientists for years. How is it that neural networks can seemingly piece together raw information to understand more complex patterns in our world?

How it worked: The researchers tried to map out a model’s “brain” by analyzing its neuron clusters, sometimes called features. First, they created a way for the AI to tell us which features get activated when we ask certain questions — sort of like how different parts of the brain light up during an MRI.

Then, they experimented with what would happen if you amplified certain features. That led to some strange behavior: When they boosted a feature of the Golden Gate Bridge, Claude got confused and decided it was “the iconic bridge itself.” But the real goal is to do just the opposite — figuring out a way to quiet certain parts of the neural network that we don’t want activated.

Why that’s important: Right now, it’s easy to get models like Claude to spew out biased, incorrect, or even dangerous information. But what if you could concoct a digital pill that suppresses the pathways that create toxic material? By deadening those areas of the network, Anthropic was able to stop Claude from generating deceptive and dangerous content — a major breakthrough toward building safer models.

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AI & TECH NEWS

Everything you need to know today

Source: Humane

  • Face Palm: The founders of Humane, whose $700 AI pin was met with scathing reviews last month, are allegedly looking to sell the company for up to $1 billion.

  • Pay to Play: Amazon is reportedly planning to release a new, AI-powered version of Alexa. But customers will need to sign up for a monthly subscription to access it.

  • No Free Rides: Google will soon include ads in the AI overviews that now appear at the top of its search results.

  • Substitute Teacher: Microsoft and Khan Academy are teaming up to release a no-cost AI teaching assistant that can help create lesson plans and test questions.

AI GENERATED IMAGES

1940s Ads

Source: u/Agentcooper1974 on Reddit

Prompt: an advertisement for [enter product and "brand" here] from 1940 --stylize 800

Ex: a commercial from 1940 for a "Snickers" candy bar. --stylize 800

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Zain & the Superhuman AI team

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