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With about 100 million tracks available and over 600 million subscribers, helping listeners find the music they will love has become a navigational challenge for Spotify. It’s the promise of personalization and meaningful recommendations that will give the vast catalog more meaning, and that is central to Spotify’s mission.

The streaming audio giant’s suite of recommendation tools has grown over the years: Spotify Home feed, Discover Weekly, Blend, Daylist, and Made for You Mixes. And in recent years, there have been signs that it is working. According to data released by Spotify at its 2022 Investor Day, artist discoveries every month on Spotify had reached 22 billion, up from 10 billion in 2018, “and we’re nowhere near done,” the company stated at that time.

Over the past decade or more, Spotify has been investing in AI and, in particular, in machine learning. Its recently launched AI DJ may be its biggest bet yet that technology will allow subscribers to better personalize listening sessions and discover new music. The AI DJ mimics the vibe of radio by announcing the names of songs and lead-in to tracks, something aimed in part to help ease listeners into extending out of their comfort zones. An existing pain point for AI algorithms — which can be excellent at giving listeners what it knows they already like — is anticipating when you want to break out of that comfort zone. 

The AI DJ combines personalization technology, generative AI, and a dynamic AI voice, and listeners can tap the DJ button when they want to hear something new, and something less-directly-derived from their established likes. Behind the dulcet tones of an AI DJ there are people, tech experts and music experts, who aim to improve the recommendation capacity of Spotify’s tools. The company has hundreds of music editors and experts across the globe. A Spotify spokesperson said the generative AI tool allows the human experts to “scale their innate knowledge in ways never before possible.”  

The data on a particular song or artist captures a few attributes: particular musical features, and which song or artist it has been typically paired with among the millions of listening sessions whose data the AI algorithm can access. Gathering information about the song is a fairly easy process, including release year, genre, and mood — from happy to danceable or melancholic. Various musical attributes, such as tempo, key, and instrumentation, are also identified. Combining this data associated with millions of listening sessions and other users’ preferences helps to generate new recommendations, and makes the leap possible from aggregated data to individual listener assumptions.

In its simplest formulation, “Users who liked Y also liked Z. We know you like Y, so you might like Z,” is how an AI finds matches. And Spotify says it’s working. “Since launching DJ, we’ve found that when DJ listeners hear commentary alongside personal music recommendations, they’re more willing to try something new (or listen to a song they may have otherwise skipped),” the spokesperson said. 

If successful, it’s not just listeners that get relief from a pain point. A great discovery tool is as beneficial to the artists seeking to build connections with new fans.

Julie Knibbe, founder & CEO of Music Tomorrow — which aims to help artists connect with more listeners by understanding how algorithms work and how to better work with them — says everyone is trying to figure out how to balance familiarity and novelty in a meaningful way, and everyone is leaning on AI algorithms to help make this possible. Be she says the balance between discovering new music and staying with established patterns is a central unresolved issue for all involved, from Spotify to listeners and the artists.

“Any AI is only good at what you tell them to do,” Knibbe said. “These recommender systems have been around for over a decade and they’ve become very good at predicting what you will like. What they can’t do is know what’s in your head, specifically when you want to venture out into a new musical terrain or category.” 

Spotify’s Daylist is an attempt to use generative AI to take into account established tastes, but also the varying contexts that can shape and reshape a listeners’ tastes across the course of a day, and make new recommendations that fit various moods, activities and vibes. Knibbe says it’s possible that improvements like these continue, and the AI gets better at finding the formula for how much novelty a listener wants, but she added, “the assumption that people want to discover new music all the time is not true.”

Most people still return, fairly happily, to familiar musical terrain and listening patterns. 

“You have various profiles of listeners, curators, experts … people put different demands on the AI,” Knibbe said. “Experts are more difficult to surprise, but they aren’t the majority of listeners, who tend to be more casual,” and whose Spotify usage, she says, often amounts to creating a “comfortable background” to daily life.

Technology optimists often speak in terms of an era of “abundance.” With 100 million songs available, but many listeners preferring the same 100 songs a million times, it’s easy to understand why a new balance is being sought. But Ben Ratliff, a music critic and author of “Every Song Ever: Twenty Ways to Listen in an Age of Musical Plenty,” says algorithms are less solution to this problem than a further entrenching of it.

“Spotify is good at catching onto popular sensibilities and creating a soundtrack for them,” Ratliff said. “Its Sadgirl Starter Pack playlist, for instance, has a great name and about a million and a half likes. Unfortunately, under the banner of a gift, the SSP simplifies the oceanic complexity of young-adult depression into a small collection of dependably ‘yearny’ music acts, and makes hard clichés of music and sensibility form more quickly.” 

Works of curation that are clearly made by actual people with actual preferences remain Ratliff’s preference. Even a good playlist, he says, might have been made without much intention and conscience, but just a developed sense of pattern recognition, “whether it’s patterns of obscurity or patterns of the broadly known,” he said.

Depending on the individual, AI may have equal chances of becoming either a utopian or dystopian solution within the 100-million track universe. Ratliff says most users should keep it more simple in their streaming music journeys. “As long as you realize that the app will never know you in the way you want to be known, and as long as you know what you’re looking for, or have some good prompts at the ready, you can find lots of great music on Spotify.” 

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China is still an important market even if investors diversify from it now, says Peak XV

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China is still an important market even if investors diversify from it now, says Peak XV

Shailendra Singh.

Lionel Ng | Bloomberg | Getty Images

China will remain an important market for investors in the long term, even if other countries are now benefiting from investments flowing out of China amid escalating tensions with the U.S., according to Peak XV Partners, formerly Sequoia Capital India and Southeast Asia.

“The China Plus One strategy, in terms of sourcing and so on, is definitely benefiting places like India, Southeast Asia,” said Shailendra Singh, managing director of Peak XV Partners, one of Asia’s biggest venture capital firms with $9 billion of assets under management.

“In the very long term, if you take a 10, 20, 30-year view, if you assume that geopolitics will find some new normal, China is going to be a huge economy, and good businesses will be built in China,” Singh told CNBC’s Tanvir Gill.

Last year, Sequoia split into three independent geographic units – Sequoia Capital in the U.S. and Europe, Peak XV Partners in India and Southeast Asia and HongShan in China. The move came amid increasingly strained relations between Washington and Beijing.

Peak XV has invested in over 400 companies in the technology, software, financial services and consumer space. They include fintech firm Pine Labs, Singapore-based online retailer Carousell, Indonesian ride-hailing giant Gojek as well as Indian edtechs Byju’s and Unacademy.

For years, China has been Asia’s technology and innovation powerhouse, being home to tech juggernauts including Alibaba Group and Tencent. It has also gained the title of being the world’s factory, producing low-cost consumer goods as well as most of the world’s iPhones and electric vehicles.

However, firms such as Apple and BMW have been diversifying their supply chains away from China amid geopolitical concerns. Apple now reportedly makes around 1 in 7, or 14%, of its iPhones in India, after stringent Covid controls in China disrupted its operations there.

While India and Southeast Asian countries have been benefiting from such diversification efforts as companies set up operations elsewhere, China will still be an important market, said Singh.

David Roche says India won't replace China's role in global trade

“All of us around the world, while India or Southeast Asia might benefit in the short term, should really be thinking about how would we work well with China in the long term,” said Singh.

David Roche, president and global strategist at Independent Strategy, said in March that India won’t replace China in global trade as the Chinese model was “based on achieving global market share” while the Indian model is “about domestic market development.”

“India will continue to make progress but it will a slow and steady progress, and not at all similar to the Chinese model,” said Roche.

The next China is not India or Vietnam — it's still China, says strategist

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Instagram co-founder Mike Krieger joins Amazon-backed Anthropic

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Instagram co-founder Mike Krieger joins Amazon-backed Anthropic

Omar Marques | Lightrocket | Getty Images

Instagram co-founder Mike Krieger will join artificial intelligence firm Anthropic as chief product officer, the company announced Wednesday.

Krieger, the former chief technology officer of Meta-owned Instagram, grew the platform to 1 billion users and increased its engineering team to more than 450 people during his time there, per a release. He and Instagram’s other co-founder, Kevin Systrom, most recently built the personalized news app Artifact and sold it to Yahoo.

Around this time last year, Anthropic had only rolled out the first version of its chatbot without any consumer access or major fanfare. Now, it’s one of the hottest AI startups, with a product that directly competes with OpenAI’s ChatGPT in both the enterprise and consumer worlds. Krieger’s hiring is likely meant to further that competition.

The generative AI startup is the company behind Claude, one of the chatbots that, like OpenAI’s ChatGPT and Google‘s Gemini, has rocketed in popularity in the past year.

“Mike will oversee Anthropic’s product engineering, product management, and product design efforts as we work to expand our suite of enterprise applications and bring Claude to a wider audience,” Anthropic said in a release.

News of Krieger’s hiring follows Anthropic’s debut of its first enterprise offering and iOS app earlier this month. And in March, Anthropic announced Claude 3, a suite of AI models that it says are its fastest and most powerful yet.

Anthropic was founded by ex-OpenAI research executives, and its backers include Google, Salesforce and Amazon. It’s closed five different funding deals totaling about $7.3 billion in the past year.

Krieger will lead Anthropic’s latest initiatives.

The company’s new plan for businesses, dubbed Team, has been in development over the last few quarters and involved beta-testing with between 30 and 50 customers across various industries, such as technology, financial services, legal services and health care, Anthropic co-founder Daniela Amodei told CNBC in an interview earlier this month.

Anthropic’s first iOS app is free for users across all plans and also debuted this month. It provides syncing with web chats and the ability to upload photos and files from a smartphone. There are plans to launch an Android app, too.

The generative AI field has exploded over the past year, with a record $29.1 billion invested across nearly 700 deals in 2023, a more than 260% increase in deal value from a year earlier, according to PitchBook. It’s become the buzziest phrase on corporate earnings calls quarter after quarter.

Academics and ethicists have voiced significant concerns about the technology’s tendency to propagate bias. But even so, it’s quickly made its way into schools, online travel, the medical industry, online advertising and more.

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These wall-climbing, AI-powered robots are finding the flaws in ‘D’ grade US infrastructure, from commuter bridges to military hardware

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These wall-climbing, AI-powered robots are finding the flaws in 'D' grade US infrastructure, from commuter bridges to military hardware

CNBC Disruptor 50 Gecko Robotics disrupts the infrastructure industry

The collapse of Baltimore’s Francis Scott Key Bridge earlier this year and an I-95 overpass in Philadelphia last June weren’t triggered by structural flaws — a runaway, powerless ocean ship and tanker fire were the culprits. But the disasters were the latest examples of an issue seen across the U.S.: trillions of dollars worth of critical — and vulnerable — bridges, roads, dams, factories, plants and machinery that are rapidly aging and in need of repair.

Significant sums of money are being spent to fix the issues, some coming from President Biden’s Infrastructure Act and other legislation, but the way infrastructure is maintained has largely not changed, mostly done slowly by humans or after a significant issue arises like a leak or collapse.

Gecko Robotics, which ranked No. 42 on the 2024 CNBC Disruptor 50 list, is taking on the nationwide challenge with AI and robots, specifically, its wall-climbing bots that perform inspections on infrastructure and not only identify existing issues but also to try to predict what can be done to avoid future problems.

More coverage of the 2024 CNBC Disruptor 50

“When you think about the built world, a lot of concrete, a lot of metal that is, especially in the U.S., 60 to 70 years old; we as a country have a D rating for infrastructure and getting that up to a B is a $4 trillion to $6 trillion problem,” Gecko Robotics CEO Jake Loosararian told CNBC’s Julia Boorstin. “A lot of that is understanding what to fix and then targeting those repairs, and then also ensuring that they don’t continue to make the same mistakes.”

Gecko Robotics’ technology is already being used to monitor “500,000 of the world’s most critical assets,” Loosararian said, which range from oil and gas facilities and pipelines to boilers and tanks at manufacturing facilities.

A focus on military hardware, from subs to aircraft carriers

Gecko robots are increasingly being utilized by the U.S. military. In 2022, the U.S. Air Force awarded Gecko Robotics a contract to help it with the conversion of missile silos. Last year, the U.S. Navy tapped the company to help modernize the manufacturing process of its Columbia-class nuclear submarine program, using Gecko’s robots to conduct inspections of welds.

Gecko Robotics is also working with the Navy to inspect aircraft carriers, which Loosararian demonstrated on CNBC via a demo on the USS Intrepid, a decommissioned aircraft carrier that now serves as a museum in New York City.

He compared the analysis that Gecko Robotics is doing on infrastructure to a CAT scan of a human body, while also creating a digital twin of the scanned object.

Those inspections historically are done by workers, collecting thousands of readings across an aircraft carrier. Gecko Robotics technology can collect upwards of 20 million data points in a tenth of the time, Loosararian said.

“There’s human error, and if you’re hanging off the side of a ship, it’s pretty dangerous too,” he said.

There are also issues related to the timeliness of military hardware construction and readiness of defense assets in an unpredictable world of global threats. For example, Loosararian said China is building ships 232 times faster than the U.S. is, a function of the sheer amount of shipbuilding capacity that China now has in comparison.

“A third of our naval vessels are in drydock right now, and you want them out of drydock or not even in a maintenance cycle,” Loosararian said. “What we’re doing with Lidar and ultrasonic sensors is a health scan, seeing what the damages are and how to fix them, because what we’re trying to do is get these ships from drydock out to the seas patrolling as fast as possible.”

The digital twins being created by Gecko robots also help with the building of future projects, saving not only time but resources and capital.

“It’s not just about how things work day-to-day but also how do you build smarter things,” Loosararian said.” If we can understand what fails in the real world, then we can figure out how to build smarter things in the future.”

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CNBC Disruptor 50 Gecko Robotics disrupts the infrastructure industry

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