According to the paper, OpenAI believes the gains from A.I. could otherwise become concentrated among a small number of companies, including firms like OpenAI itself. The document warns that without intervention, A.I. could widen inequality by rewarding those already positioned to benefit while leaving other workers and communities behind. 

The company’s proposal goes beyond broad rhetoric. In the document, OpenAI says a public fund could be seeded through cooperation between policymakers and A.I. companies, then invested in long-term assets tied both to A.I. firms and to the wider economy adopting the technology. Returns from that fund, it says, could be distributed directly to citizens, giving more Americans a share of A.I. wealth regardless of whether they already own stocks or other financial assets. 

OpenAI also argues that the tax system may need to change as A.I. shifts economic activity away from wages and toward corporate profits, capital gains and automated labor. The paper says policymakers could respond by increasing reliance on capital-based taxes, considering targeted levies on sustained A.I.-driven returns and exploring taxes related to automation, while preserving funding for programs such as Social Security, Medicaid and housing assistance. 

The proposal is notable not only because of its ambition, but because it comes from one of the companies racing to build the technology likely to cause the disruption. OpenAI describes the paper as an early, exploratory set of ideas rather than a final blueprint, but its message is clear: if A.I. creates enormous wealth, the public should not be left watching from the sidelines.

Apple said the anniversary program began on March 13 with Alicia Keys at Apple Grand Central in New York and closed on March 31 with a performance by Sir Paul McCartney at Apple Park in Cupertino, part of a broader push to frame the company’s half-century mark around “creativity, innovation, and impact.” 

In Cupertino, Apple closed the month with Paul McCartney at Apple Park, a symbolic finale given Steve Jobs’ long-documented admiration for the Beatles. 

Cupertino Apple Park stage

Paul McCartney performs at Apple Park in Cupertino, the grand finale of Apple’s 50th anniversary celebrations

Tim Cook greets the crowd at Apple Park

In New York, Alicia Keys opened the celebrations from the steps of Apple Grand Central, with Apple highlighting the show as both a live performance and a showcase for iPhone 17 Pro capture. 

Alicia Keys kicks off Apple’s 50th anniversary celebrations with a live performance atop Apple Grand Central’s iconic steps

Customers fill Apple Grand Central for a special event on March 13

Tim Cook and Alicia Keys greet the audience at Apple’s 50th anniversary celebration in New York City

In London, Apple Battersea hosted Mumford & Sons and a DJ set from Nia Archives, linking the anniversary to the U.K.’s live music scene. 

London in honor of Apple’s 50th anniversary

In Paris, Apple Champs-Élysées turned the spotlight on French touch, with a pop-up recording studio, Today at Apple sessions, and performances from artists including Breakbot and Cassius. 

Apple Champs-Élysées hosts a live performance with French touch pioneers such as Breakbot and Cassius, alongside the next generation, including disiz, Ebony, Rnboi, and Guy2Bezbar, with DJ sets by Paloma Le Friant, Andy 4000, and more

In Shanghai, Apple Jing’an became part of Shanghai Fashion Week through a Feng Chen Wang show themed “Life and Love.” 

As part of Shanghai Fashion Week, designer Feng Chen Wang presented a special show at Apple Jing’an themed “Life and Love,” celebrating Apple’s 50th anniversary and the company’s spirit of thinking different

In Chengdu, Apple Taikoo Li Chengdu featured a performance from Chinese pop star Chris Lee, whom Apple positioned as a cultural figure spanning music, fashion, and art. 

Chris Lee performs at Apple Taikoo Li Chengdu in honor of Apple’s 50th anniversary

In Mumbai, Apple BKC unveiled a mural by Mira Felicia Malhotra and paired it with a conversation featuring singer-songwriter Anuv Jain.

At Apple BKC in Mumbai, a playful mural by visual artist and illustrator Mira Felicia Malhotra pays tribute to the city’s vibrant creative community

 In Tokyo, Apple Omotesando hosted virtual artist Mori Calliope for a live performance and discussion about her creative process inside Apple’s ecosystem. 

Virtual artist Mori Calliope performs at Apple Omotesando in Tokyo for a celebration of creativity and technology

In Vancouver, Apple Pacific Centre featured figure skater Elladj Baldé, who used a Today at Apple session to discuss his iPhone-shot “Wild Ice” work.

In a special Today at Apple session, Canadian figure skater Elladj Baldé discussed his creative journey with his “Wild Ice” series

 In Mexico City, Apple Antara gathered talent from Apple TV productions including Las Azules, Acapulco, and Midnight Family for a conversation about local storytelling with global reach.

Apple Antara brought together talent behind the hit Apple TV productions Las Azules, Acapulco, and Midnight Family for an intimate conversation about creativity and storytelling

 In Washington, D.C., Apple Carnegie Library centered accessibility, with Troy Kotsur, Roberta Cordano, and Haben Girma discussing Deaf creativity and inclusive technology.

Troy Kotsur and Roberta Cordano join Apple’s Sarah Herrlinger at Apple Carnegie Library in Washington, D.C., for a discussion about the legacy and future of Deaf creativity

 In Sydney, the Sydney Opera House became a giant canvas for “Illuminating Creativity,” projecting artwork from emerging Australian artists and members of the public to a score composed in Logic Pro.

Illuminating Creativity transforms the Sydney Opera House’s eastern Bennelong sails into a canvas to showcase digital artwork from 11 emerging Australian artists and six members of the public

 In Bangkok, Apple Iconsiam featured artist Molly Yllom and her Crybaby universe in a special Today at Apple session.

To celebrate Apple’s 50th anniversary, Molly Yllom — the artist behind the Crybaby universe — led a special Today at Apple session at Apple Iconsiam in Bangkok

 In Seoul, Apple Myeongdong welcomed K-pop group CORTIS for a fan conversation and live performance. 

K-pop sensation CORTIS performs at Apple Myeongdong in Seoul as part of Apple’s 50th anniversary celebrations

The message behind the anniversary was clear: Apple wanted its 50th birthday to feel less like a retrospective and more like a demonstration of how tightly its products are woven into today’s creative industries, from recording studios and fashion runways to accessibility tools and public art. That framing also matches Apple’s own description of the milestone, with the company saying it remains focused on “the future” as it moves beyond its first half-century.

Photos: Apple

The threat carries more weight because at least one major U.S. cloud operator has already been affected. Reuters reported on April 1, citing the Financial Times and a person familiar with the matter, that Amazon’s cloud computing operation in Bahrain was damaged after an Iranian strike. In earlier reporting, Reuters said drone strikes had damaged Amazon Web Services data centers in both the United Arab Emirates and Bahrain, disrupting cloud services and underscoring the risks facing tech infrastructure in the region. 

The latest warnings mark a sharp broadening of the conflict’s impact on the technology sector, especially as global cloud and AI infrastructure increasingly depends on Gulf-based capacity. Reuters has separately reported that rising instability in the Middle East is already testing Big Tech’s 2026 AI spending plans, with companies such as Amazon, Microsoft, Alphabet and Meta exposed to higher energy and infrastructure risk. The Associated Press also reported that U.S. tech firms operating in the region are now facing direct threats as the war widens.

Business Insider reported that affected staff began receiving emails around 6 a.m. ET and were then quickly locked out of internal systems. In the email reviewed by the publication, Oracle told workers,

“After careful consideration of Oracle’s current business needs, we have made the decision to eliminate your role as part of a broader organizational change. As a result, today is your last working day.”

Posts from laid-off employees indicate the cuts touched Oracle Health, Sales, Cloud, Customer Success and NetSuite, underscoring that this was not limited to a single division. Oracle has not publicly detailed the total number of jobs eliminated, but the move comes as the company ramps up spending on AI data centers and broader restructuring.

Officials from nine countries, including the United States, France, Poland, the United Arab Emirates and Morocco, presented national approaches to bringing technology into education systems, underscoring how AI policy is increasingly moving from research labs into classrooms and public-sector strategy. The White House said the summit brought together policymakers and private-sector leaders as governments treat AI not only as a learning tool, but also as an economic and geopolitical priority.

In her keynote, Melania Trump outlined what she called three forces likely to shape the next generation: AI-driven personalized learning, the emergence of humanoid educators for at-home use, and the broader role of technology and education in economic growth.

“The future of AI is ‘personified’ – it will be formed in the shape of humans,”

Melania Trump said.

Very soon, artificial intelligence will move from our mobile phones to humanoids that deliver utility.”

Melania Trump also used the summit to introduce what the White House described as an American-built humanoid system, Figure 3, calling it “my first American-made humanoid guest in the White House.” The administration said the appearance marked the first formal presentation of that kind of technology to international leaders in a diplomatic setting at the White House, turning the summit into a demonstration of how embodied AI may become part of future education, home assistance and public-facing services.

The First Lady framed that future in distinctly consumer-tech terms. She asked attendees to “imagine a humanoid educator named ‘Plato,’” describing an always-available AI system able to adapt lessons in real time to a student’s pace, prior knowledge and even emotional state.

“Plato will provide a personalized experience, adaptive to the needs of each student. Plato is always patient, and always available,”

Melania Trump said, while adding that

“we must balance our tech optimism with caution. The safety of our next generation is always paramount.”

Melania Trump also made a broader industrial argument, urging closer coordination between government and the private sector. Referring to the State Department session, she highlighted participation from companies including Meta, Microsoft, OpenAI, X, Palantir, Google, Zoom and Adobe, and said,

“We can accelerate civilization’s march forward when enterprise delivers innovation, government creates scale, and our capital markets finance the distribution of these emerging technologies.”

The summit fits into a larger White House push around AI-enabled education. The coalition’s stated goal is to help children learn, grow and thrive through the safe and innovative use of advanced technology, while expanding access to tools and pairing those deployments with digital safety measures.

At its core, the event was both a diplomatic exercise and a signal about where parts of the policy conversation around AI are heading next: away from abstract debate over models alone, and toward real-world systems that mix software, hardware, education and national competitiveness.

“We stand at a turning point because of artificial intelligence – The Age of Imagination,”

Melania Trump said.

“This technology may reset the modern world order and rebalance power.”

Image: Official video posted on the White House website (screenshot)

He stated he’s pursuing this project because semiconductor manufacturers are not producing chips fast enough to meet his companies’ AI and robotics demands. Musk said:

“We either build the Terafab or we don’t have the chips, and we need the chips, so we build the Terafab.”

According to Bloomberg Musk shared his plans during an event in downtown Austin, Texas, with a photo indicating that the “Terafab” facility will be “gigafactory,” located near Tesla’s Austin headquarters.

He also added that the aim is to produce chips capable of supporting 100–200 gigawatts of computing power annually on Earth, as well as one terawatt in space. He did not provide a timeline for the plan.

Image: Presentation of the Terafab project

Formula 1 has always sold itself as the pinnacle of motorsport. That description still fits, but it no longer goes far enough. In 2026, F1 is better understood as one of the world’s most compressed and visible innovation environments, a place where artificial intelligence, cloud computing, advanced fuels, digital twins, real-time analytics, and high-performance engineering converge under conditions that leave no room for delay, redundancy, or imprecision. The sport is still about speed. But increasingly, speed is the output of something bigger: a technology stack. 

That is what makes Formula 1 so compelling for professional technology and innovation media. Unlike many sectors where experimentation happens quietly inside labs or behind enterprise procurement cycles, F1 innovation unfolds in public. It is measurable in lap time, visible in race strategy, constrained by regulation, and judged every weekend against the toughest benchmark available: competitive performance. Every design choice, every model, every simulation, and every operational decision must stand up not in theory, but in motion.

Why the 2026 Rules Matter

The sport’s next chapter makes that clearer than ever. Formula 1’s 2026 rules package is one of the largest technical resets in years, built around redesigned cars, active aerodynamics, smarter energy deployment, and advanced sustainable fuels. Formula1.com says the new era will bring cars that are more challenging for teams and drivers, while relying on “advanced sustainable fuel and smarter energy use.” The new fuels themselves are made from sources such as carbon capture, municipal waste, and non-food biomass, and Formula 1 says they are independently certified to meet strict sustainability standards. 

This matters because Formula 1 is no longer innovating in isolated technical categories. It is innovating across systems. The crossing point between technology and innovation in F1 is not simply the car. It is the way mechanical engineering, software, energy systems, manufacturing, logistics, and media now operate as one connected performance architecture. A faster car still matters, of course, but so does the quality of the simulation environment that predicted its behavior, the cloud infrastructure that processed its data, the machine-learning tools that surfaced anomalies, and the human-machine workflows that turned data into decisions on race day. 

AI, Cloud, and the Race Weekend Brain

In that sense, Formula 1 increasingly resembles the broader economy. Many modern industries are moving toward software-defined operations, where physical assets are shaped by digital models and strategic advantage comes from linking data, compute, and execution. F1 just gets there first, and under more intense conditions.

One of the clearest examples is the sport’s deepening use of AI and cloud technologies. Through its work with AWS, Formula 1 has been building tools that do far more than decorate a broadcast. AWS says F1’s Track Pulse uses machine learning and generative AI to give the broadcast team a clearer real-time picture of on-track action, including live driver battles, top speeds, and predictive storytelling cues. This is significant not only as a fan product, but as evidence of how AI is changing the way complex live systems are interpreted and packaged. In a data-rich environment, the challenge is no longer collecting information. It is deciding what matters in time to act on it. 

Digital Twins and Simulation at Speed

That same principle applies even more sharply inside teams. The modern F1 operation is saturated with telemetry, historical comparisons, environmental variables, and strategic possibilities. The competitive edge comes from filtering that information intelligently and turning it into high-confidence decisions in seconds. McLaren’s work with Deloitte offers a strong example of this shift. Deloitte says it helped advance McLaren’s digital twin simulation technology to run 30,000 simulations per second while extracting actionable insights from more than a million data points captured during each race. On race day, that simulation environment can analyze millions of possible scenarios and help shape calls on pit stops, tire strategy, and fuel management. 

That is not motorsport as most audiences once understood it. It is operational intelligence in a high-speed setting. And it closely mirrors where many technology-intensive businesses are heading: toward decision environments in which digital twins, scenario modeling, and real-time analytics support human judgment rather than replace it. Formula 1 demonstrates that innovation is not just about building better systems; it is about building systems that help people make better decisions under pressure.

Sustainability as a Performance Challenge

The 2026 rule changes also reinforce F1’s growing role as a laboratory for the energy transition. Formula 1’s own sustainability material makes clear that advanced sustainable fuel is not a side project or symbolic gesture. It is embedded in the sport’s larger decarbonization strategy. According to Formula 1’s 2025 Sustainability Update, the sport had reduced its carbon emissions by 26% by the end of 2024 compared with its 2018 baseline, despite substantial growth in races, attendance, and audience. The report says Formula 1 is “on track” for its Net Zero by 2030 target, and notes that from 2026 advanced sustainable fuel will be introduced in Formula 1 cars as part of a broader effort that also includes green energy, logistics changes, and sustainable aviation fuel. 

This is where Formula 1’s innovation model becomes especially relevant beyond racing. In many sectors, sustainability is still handled as a compliance layer added after the core engineering work is done. In F1, sustainability is increasingly becoming a design constraint and a performance problem to solve. The fuel cannot simply be cleaner on paper; it must work at the highest level of competition. It must operate in engines built for extreme stress. It must satisfy engineers, suppliers, regulators, and manufacturers at the same time. Formula 1’s explanation of the new fuels emphasizes that they are “drop-in” fuels, designed to replace fossil equivalents without requiring engine redesign in road-relevant contexts. That does not mean F1 alone will transform global transport, but it does mean the sport is helping move sustainable-fuel development from concept to credibility.

The Car as an Integrated System

The same can be said of aerodynamics and vehicle systems. Formula 1’s 2026 framework is designed not only to preserve speed, but to rethink how speed is generated and managed. Active aero, tighter energy management, and new control tools shift the competitive focus toward more dynamic system optimization. This makes the car itself more software-mediated and the race weekend more analytically demanding. Teams will have to balance aerodynamic efficiency, energy deployment, and racecraft in ways that make integrated systems thinking more important than ever.

That evolution is easy to miss if F1 is viewed only through its glamour or its spectacle. But from a technology standpoint, it is one of the sport’s most important transitions. The old image of Formula 1 innovation was built around visible hardware breakthroughs: dramatic wings, exotic materials, iconic engines. The new image is more distributed. It includes simulation environments, machine-learning layers, cloud-native collaboration, sustainability engineering, and the increasingly sophisticated translation of race data into decisions and products.

Innovation Beyond the Garage

Even the fan experience now reflects that shift. Formula 1 is not just building faster cars; it is building a smarter media platform around the race itself. The AWS-F1 partnership shows how digital infrastructure and AI are being used not merely to report what happened, but to anticipate storylines, visualize complex race dynamics, and make a highly technical sport more legible in real time. That has implications far beyond entertainment. It points to a future in which data-heavy environments, from industrial operations to financial systems, increasingly rely on AI-assisted narrative layers to help human users understand fast-changing conditions. 

There is also a business lesson in the way Formula 1 structures innovation. Contrary to the popular assumption that more resources automatically produce better outcomes, F1 thrives on constraints. Development is limited by financial rules, technical rules, and testing restrictions. That forces efficiency. It rewards teams that build tighter feedback loops between modeling and reality, between design and manufacturing, between operations and post-race learning. In the wider technology economy, where many organizations are trying to do more with less while still delivering transformation, that discipline may be one of Formula 1’s most transferable advantages. 

Why F1 Matters to the Innovation Economy

This is why Formula 1 deserves to be taken seriously not only as a motorsport property, but as a strategic lens on innovation itself. It shows what happens when multiple technologies mature at once and are forced to interact in a real-world system. It shows how AI becomes useful when attached to urgent decisions. It shows how sustainability becomes meaningful when it is tied to performance. It shows how digital twins become valuable when they inform actions rather than dashboards. And it shows how competitive pressure can accelerate the fusion of software, hardware, energy, and experience design.

Formula 1 is often described as the future arriving early. In 2026, that idea feels less like a slogan and more like an operating model. At the crossing point of technology and innovation, Formula 1 is no longer simply a showcase for advanced engineering. It is a proving ground for how modern systems are built, optimized, and understood. For anyone trying to track where high-performance innovation is really heading, the paddock is no longer a niche place to look. It is one of the best places to start. 

Images: Formula1.com News

Speaking on this week’s episode of the Equity podcast, Mowry said the era of easy traction for simple LLM-based products is largely over. Startups that rely almost entirely on back-end models such as OpenAI’s GPT family, Anthropic’s Claude or Google DeepMind’s Gemini without building meaningful intellectual property of their own are unlikely to see durable growth.

The End of the “Slap a UI on GPT” Era

LLM wrappers — startups that package an existing large language model with a user interface or workflow to solve a specific problem — once attracted rapid user growth. In mid-2024, when OpenAI launched its ChatGPT store, it was possible to gain attention by layering a clean UX on top of a powerful foundation model.

But that window has narrowed.

“If you’re really just counting on the back-end model to do all the work and you’re almost white-labeling that model, the industry doesn’t have a lot of patience for that anymore,”

Mowry said. Wrapping “very thin intellectual property around Gemini or GPT-5” signals a lack of differentiation, he added.

AI Is Redefining Startup Economics, Says Microsoft VP

The implication is clear: sustainable AI startups must build deeper product value, proprietary data, or vertical specialization. Otherwise, they risk being commoditized as foundation models improve and expand their own feature sets.

Why AI Aggregators Are Under Pressure

A subset of wrappers — AI aggregators — may face even steeper challenges. These companies combine multiple large language models into a single interface or API layer, routing queries across providers while offering monitoring, governance or evaluation tools.

Examples include AI search startup Perplexity AI and developer platform OpenRouter, which gives developers access to multiple AI models through one API.

While such platforms have gained visibility, Mowry’s advice to incoming founders is direct:

“Stay out of the aggregator business.”

According to Mowry, aggregators are not seeing strong growth or progression because users increasingly expect built-in intellectual property — smart routing based on real understanding of context and need — rather than simple model switching driven by compute availability or access constraints.

In his view, startups must build “deep, wide moats that are either horizontally differentiated or something really specific to a vertical market” to progress and grow.

A Familiar Pattern from the Early Cloud Era

Mowry draws a parallel with the early days of cloud computing in the late 2000s and early 2010s, when Amazon Web Services began to take off. At the time, numerous startups emerged to resell AWS infrastructure, positioning themselves as simpler gateways that offered billing consolidation, tooling and support.

But as Amazon Web Services built its own enterprise tools and customers became more sophisticated in managing cloud services directly, many of those resellers were squeezed out. The companies that survived were those that added real, defensible services such as security, migration expertise or DevOps consulting.

AI aggregators today face similar margin pressure. As model providers expand into enterprise features — including governance, monitoring and orchestration — middle layers that do not offer strong differentiation risk being sidelined.

Where Mowry Sees Opportunity

Despite his warnings, Mowry remains bullish on several AI-driven categories.

One is the wave of “vibe coding” and AI-native developer platforms. In 2025, startups such as Replit, Lovable and Cursor— all Google Cloud customers, according to Mowry — attracted significant investment and customer traction. These companies go beyond basic model access, embedding AI deeply into developer workflows and building sticky ecosystems around their tools.

Cursor, for example, represents what Mowry considers a stronger type of LLM wrapper: a GPT-powered coding assistant tightly integrated into software development environments, with product depth that extends well beyond a simple interface layer.

He also points to vertical AI plays such as Harvey AI, which targets the legal industry with specialized functionality. These startups build domain-specific capabilities, workflows and datasets that create defensible advantages.

Mowry expects continued growth in direct-to-consumer AI as well. He highlights the opportunity for creative students to use Google’s AI video generator Veo to bring stories to life — an example of powerful generative tools moving into the hands of everyday users.

Beyond AI infrastructure and applications, he sees biotech and climate tech as having a moment. Both sectors are benefiting from increased venture investment and unprecedented access to large datasets, enabling startups to create value in ways that were previously impossible.

The Bar for AI Startups Is Rising

The broader message from Mowry is not that AI opportunity is shrinking — but that it is maturing. As foundation models become more capable and cloud providers move up the stack, superficial differentiation is no longer enough.

Startups that merely wrap existing LLMs without building proprietary technology, deep integrations or vertical expertise may struggle to justify their existence. Those that develop meaningful intellectual property, embed themselves into critical workflows or harness unique data, however, could still define the next generation of AI companies.

Material by Iva Abadjievа

Image: Darren Mowry’s LinkedIn profile

What’s New for Users

One of the most visible additions arrives in Apple Music. iOS 26.4 introduces an AI-powered “Playlist Playground” feature built on Apple Intelligence. Users can generate a custom 25-song playlist from a simple text prompt such as “upbeat workout mix” or “calm evening.” The playlist can then be refined further, with the option to select matching cover art, offering a more personalized discovery experience.

Apple Music is also gaining a new “Concerts Near You” section designed to surface live shows from favorite artists. The feature allows filtering by date and genre, and users can switch locations when traveling, strengthening Apple’s push into music discovery and live event engagement.

In podcasts, Apple is responding to the broader industry’s shift toward video. The native Apple Podcasts app now allows seamless switching between audio and video episodes within the same show. Creators can publish video podcasts using HTTP Live Streaming (HLS), while listeners can move between formats instantly, including expanding to a full horizontal video display.

A new video podcast experience enabled by HLS technology lets users switch between watching and listening, move to a horizontal full display, as well as download videos for offline viewing.

Messaging is receiving a notable security-focused upgrade with encrypted Rich Communication Services (RCS), now entering testing in iOS 26.4. The end-to-end encryption aims to eventually secure conversations between iPhone and Android users at a level comparable to iMessage. For now, encrypted RCS is being tested between iPhones in beta, with conversations clearly labeled as encrypted. Apple says broader public support across iOS, iPadOS, macOS and watchOS will arrive in a later update, and availability will vary by device and carrier.

Security enhancements extend further. Stolen Device Protection is now enabled by default, adding additional biometric authentication requirements for sensitive actions such as accessing saved passwords or modifying account settings. By expanding the use of Face ID or Touch ID verification, Apple aims to reduce the risk of unauthorized access if a device is stolen and a passcode is compromised.

Drivers using Apple CarPlay will also see updates. CarPlay now supports in-car video playback for select apps, including Apple TV app, though only when the vehicle is parked to maintain safety standards. The feature introduces new entertainment options for passengers during stops or extended waits.

Developer and Enterprise Enhancements

The beta release builds on the AI features first introduced earlier in the iOS 26 cycle, refining contextual suggestions, system-wide writing assistance and predictive automation tools. Apple has also adjusted notification management and Focus mode behaviors to reduce friction across productivity workflows, while optimizing battery performance under heavier AI-related processing loads.

For developers, iOS 26.4 includes updates to SDK frameworks, improved debugging tools and expanded testing support for apps integrating advanced machine learning models. The release notes highlight fixes to SwiftUI rendering, enhancements to background execution policies and improved compatibility with third-party extensions.

Enterprise users are also seeing incremental updates aimed at device management and security compliance. Apple has patched several vulnerabilities and strengthened sandbox protections, reinforcing its positioning around secure mobile deployments for corporate environments.

As with any public beta, Apple cautions users that performance inconsistencies and app compatibility issues may occur. Developers are encouraged to test applications thoroughly before the final release candidate is issued.

Material by Veronika Atanasova

Image 1: Apple Newsroom

Image 2: Apple, iOS

The statement came alongside broader comments about how Spotify is leveraging artificial intelligence to accelerate development cycles and increase product velocity. The streaming platform shipped more than 50 new features and updates throughout 2025, and in recent weeks alone rolled out AI-driven capabilities such as AI-powered Prompted Playlists, Page Match for audiobooks, and About This Song.

Central to this transformation is an internal system called “Honk,” which Spotify engineers use to speed up coding and deployment. The system enables remote, real-time code generation and deployment using generative AI — specifically Claude Code, Söderström explained during the call.

As a concrete example, an engineer at Spotify on their morning commute from Slack on their cell phone can tell Claude to fix a bug or add a new feature to the iOS app,

Söderström said.

And once Claude finishes that work, the engineer then gets a new version of the app, pushed to them on Slack on their phone, so that he can then merge it to production, all before they even arrive at the office.

Spotify credited the system with accelerating both coding and deployment “tremendously.”

Looking ahead, Söderström made clear the company sees this as only the beginning of AI’s impact.

We foresee this not being the end of the line in terms of AI development, just the beginning,

he said.

Beyond internal productivity gains, Spotify is also investing in proprietary data advantages. Söderström highlighted the company’s efforts to build a unique dataset around music preferences — something he argued cannot be commoditized by large language models in the same way as general knowledge sources like Wikipedia.

Because there is rarely a single factual answer to music-related questions — such as what qualifies as workout music — responses vary by taste and geography. Americans may lean toward hip-hop, millions prefer death metal, while parts of Europe favor EDM and Scandinavia shows a strong preference for heavy metal.

This is a dataset that we are building right now that no one else is really building. It does not exist at this scale. And we see it improving every time we retrain our models,

Söderström noted.

Analysts on the call also pressed the company on AI-generated music. Spotify said it allows artists and labels to indicate in a track’s metadata how a song was created, while continuing to police the platform for spam and abuse.

Material by Iva Abadjievа

IMAGE: Spotify Newsroom – Stream On 2023