Duolingo: The language-learning app is pushing the boundaries of AI

6/27/23 8:00PM

Influencer app‍

‍Time magazine has released its latest list of 100 Most Influential Companies. Many of the usual suspects appear in the rankings — Apple, Chipotle, Disney — but one company in particular caught our eye.

With hundreds of millions of downloads, gamified language-learning app Duolingo was named in the prestigious Leaders section of Time’s list. The app, which has helped millions of users learn languages — and perhaps annoyed just as many with its notoriously persistent push notifications — was praised for its incorporation of AI, having been powered by its own model, Birdbrain, for years. But more recently, the company is incorporating new AI tools into its products, such as GPT-4, allowing users scenario-based ways to practice, like going furniture shopping, asking a friend to go for a hike or ordering coffee at a café in Paris.

‍It’s all a game

‍Back in 2009, Guatemalan entrepreneur Luis Von Ahn had just sold his online authentication software reCAPTCHA to Google. Keen to develop a product in the world of education, von Ahn teamed up with computer scientist Severin Hacker and founded Duolingo just 2 years later.

In a competitive space, Duolingo carved out its niche by gamifying the learning experience wherever possible. Leaderboards, experience points, levels, the pressure to keep your “streak” going, and even an in-game currency, have helped the app build habits for users — all communicated through endless notifications on your phone. Annoying? Maybe. Effective? Definitely. Per the latest count, some 20.3 million people use the app everyday.

Jon Keegan9h

DeepSeek releases new V4 series models highlighting efficiency and long context

Chinese AI lab DeepSeek has released a major new version of its eponymous open-source AI models that are nipping at the heels of leading frontier models in some areas.

The most significant DeepSeek-V4 Pro and DeepSeek-V4 Flash both have a 1 million-token context — the amount of information the model can actively work with in a single session — which is a crucial feature for complex, long-running coding tasks.

DeepSeek rebuilt how the models process information under the hood, making them substantially more efficient — and that efficiency is what makes the large context window actually usable.

Also, the new models’ coding skills have closed the gap with the major frontier models from Anthropic, OpenAI, and Google.

The authors of the model acknowledge some of V4’s shortcomings, such as its lower scores on reasoning benchmarks, saying that V4 “trails state-of-the-art frontier models by approximately 3 to 6 months.”

As open-weight models, V4 can be run on any user’s own hardware, making the V4 models among the top-performing open-source models out there. V4’s large context and token efficiency are especially significant among open-source models.

But like with earlier DeepSeek models, don’t ask it about Tiananmen Square.

DeepSeek Unveils Flagship AI Model a Year After Breakthrough

DeepSeek rebuilt how the models process information under the hood, making them substantially more efficient — and that efficiency is what makes the large context window actually usable.

Also, the new models’ coding skills have closed the gap with the major frontier models from Anthropic, OpenAI, and Google.

But like with earlier DeepSeek models, don’t ask it about Tiananmen Square.

$28.5T

Rani Molla9h

SpaceX thinks its total addressable market (TAM) is a whopping $28.5 trillion for its businesses, according to an S-1 filing for its upcoming IPO reviewed by Reuters. And most of that market isn’t rockets. The company says roughly 90% could come from AI — largely selling artificial intelligence tools to businesses.

“We believe that our enterprise strategy, which is focused on serving the digital needs of the world’s largest industries with Al solutions, positions us competitively to pursue this rapidly ⁠growing opportunity,” SpaceX said in the filing. “We believe we have identified the largest actionable total addressable market in human history.”

TAM, of course, assumes capturing every possible customer. But even a small slice of a $28.5 trillion market would be enormous.

Rani Molla11h

Tesla Cybercab production has begun

On Tesla’s earnings call earlier this week, CEO Elon Musk said production of the company’s steering-wheel-less Cybercab had begun. Since then, Musk and Tesla have posted videos showing the gold two-seater rolling off the line at its Texas Gigafactory and onto the road.

Cybercab has started production pic.twitter.com/MAeswanf96
— Elon Musk (@elonmusk) April 24, 2026

The Cybercab — meant both for consumers and Tesla’s Robotaxi network — is widely seen as central to the company’s future. “The future of the company is fundamentally based on large-scale autonomous cars and large scale and large volume, vast numbers of autonomous humanoid robots,” Musk said last year.

Whether these cars actually make it to consumers is another question. For now, regulations generally require steering wheels, and Tesla still has to prove the vehicles can reliably drive themselves.

In formation pic.twitter.com/7qA0SluL8J
— Tesla Robotaxi (@robotaxi) April 24, 2026

On the earnings call, Musk said production would be “very slow” but would ramp up and go “kind of exponential towards the end of the year and certainly next year.”

Rani Molla11h

Meta signs deal to use Amazon Graviton chips

Meta said it will deploy “tens of millions” of Amazon Web Services Graviton CPU cores to power so-called “agentic” AI systems — tools that can reason, plan, and act on their own. The move makes Meta one of the largest customers of Amazon’s in-house chips.

The deal also underscores a broader shift in AI infrastructure, as companies move beyond Nvidia GPUs and use different chips for different tasks.

Meta, which is working on its own custom inference chips, also has chip deals with Advanced Micro Devices and Nvidia.

Meta Partners With AWS on Graviton Chips to Power Agentic AI

The deal also underscores a broader shift in AI infrastructure, as companies move beyond Nvidia GPUs and use different chips for different tasks.

Meta, which is working on its own custom inference chips, also has chip deals with Advanced Micro Devices and Nvidia.

Rani Molla12h

Oracle rises after Wedbush’s Dan Ives calls the stock a buy with 25% upside

Oracle extended its premarket gains Friday after Wedbush Securities’ Dan Ives initiated coverage with an “outperform” rating and a $225 price target — about 25% upside to its pre-initiation level — calling the enterprise software and cloud infrastructure company a “foundational infrastructure provider for the AI revolution.”

Ives argues investors are misreading Oracle’s heavy capital spending and negative free cash flow as risky, despite being backed by a massive $553 billion backlog of contracted demand. He says the company’s “secret sauce” is a two-part strategy: building high-performance cloud infrastructure for AI workloads while connecting those models directly to companies’ own data.

“We believe Oracle is in the early innings of a significant repositioning as it executes on this generational opportunity,” Ives wrote.