There aren’t a lot of details on the project. Ive reportedly met Altman through Brian Chesky, the CEO of Airbnb, and the project is being funded by Ive and the Emerson Collective, Laurene Powell Jobs’ company. The New York Times claims it could raise $1 billion in funding by the end of the year, but makes no mention of Masayoshi Son, the SoftBank CEO rumored last year to have invested $1 billion in the project.
The project only has 10 employees currently, but they include Tang Tan and Evans Hankey, two key people who worked with Ive on the iPhone. As for the device itself? Last year it was rumored to be inspired by touchscreen technology and the original iPhone, which makes sense given Tan’s and Hankey’s involvement.
There’s still no timeline on when we’ll learn more about this project, but the little information dropped in the New York Times should sound very familiar to anyone following the AI hardware scene over the last year:
Mr. Altman and Mr. Ive talked about how generative A.I. made it possible to create a new computing device because the technology could do more for users than traditional software since it could summarize and prioritize messages, identify and name objects like plants and eventually field complex requests like booking travel.
Apple finally introduced the new iPhone 16 series earlier this month. The Cupertino tech giant has now begun shipping the new iPhones to the early buyers. As soon as the iPhone 16 started shipping, the first teardown video of the iPhone 16 Pro surfaced online. YouTube channel REWA Technology has posted a teardown video of the iPhone 16 Pro, which gives us a sneak peek at all the internals of the new iPhone.
The teardown shows that Apple has made a lot of design changes under the hood of the new iPhones. Notably, another YouTube channel Disassembling Parts has posted a teardown of the iPhone 16 Pro Max variant.
iPhone 16 Pro teardown reveals a compact and more densely packed motherboard
As you can see in the teardown video below, the iPhone 16 Pro features a considerably smaller motherboard. Compared to the iPhone 15 Pro, the motherboard on the 16 Pro is smaller and is more densely packed. Furthermore, the overall layout of the components is quite different. The new iPhone 16 Pro model also features better heat dissipation too. However, the tighter space could make repairs harder.
A metal-encased battery, larger camera assembly, and non-removable Camera Control button
Furthermore, the iPhone 16 Pro video reveals that Apple has packed the phone with a metal-encased battery. This is expected to aid with heat dissipation. Also, the 3,582mAh battery is 9.4 percent larger than the 3,274mAh power-cell of its predecessor.
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The teardown shows that the camera assembly on the iPhone 16 is larger than the one on its predecessor. This is due to the inclusion of the 12MP periscope telephoto lens. However, the selfie camera module is slightly smaller this time around.
The video also reveals that the new Camera Control button is non-removable as it is laser welded. Also, the company has separated the microphone from the charging port. The inner shell of the new iPhone is made from aluminum and graphite.
iPhone 16 Pro Max teardown reveals its battery is still encased in black foil
The iPhone 16 Pro Max’s teardown video shows that the bigger phone’s battery is still encased in black foil. You may be wondering why this one’s battery isn’t encased in steel. Well, this is due to the large size of the iPhone 16 Pro Max, which automatically provides better heat dissipation. Since there’s a lot more internal room, the company could get by without putting the phone’s battery in a steel case.
Generative AI is the single dominant trend in data management and analytics. Nothing else is even close.
It’s been that way since OpenAI launched ChatGPT in November 2022. The technology marked a significant improvement in the capabilities of large language models (LLMs) and showed the transformative potential of GenAI in the enterprise.
One key possibility is to be assistive in nature, with GenAI-powered natural language processing enabling virtually any employee — not just data scientists and other analysts — to use business intelligence tools to inform decisions. Due to the complex nature of most data management and analytics platforms, computer science skills, statistical expertise and data literacy training were all prerequisites before generative AI reduced those obstacles.
Another key possibility that has made generative AI such a singular data and analytics trend is exponentially improved efficiency. Generative AI applications can be trained to be agents unto themselves that take on time-consuming, repetitive tasks that data engineers and other experts previously needed to do manually.
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But while GenAI first became a major trend because of its potential, it is evolving.
ChatGPT’s launch was closely followed by the development and release of a spate of competing LLMs. Initially, the technology’s transformative capabilities were theoretical. Now, they are becoming a reality, according to Yasmeen Ahmad, Google’s managing director of strategy and outbound product management for data, analytics and AI.
Now, vendors including Google are developing generative AI tools to better enable customers to use their platforms to build GenAI models and applications. Enterprises, meanwhile, are taking advantage and creating pilot models while going through the proof-of-concept phase.
Generative AI, however, doesn’t exist in a vacuum. As a result, enterprises are emphasizing complementary capabilities such as data quality and data governance, which aim to ensure that the information feeding and training GenAI can be trusted. In addition, real-time data and automation are key to making sure that generative AI isn’t a reactive technology.
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Yasmeen Ahmad
Ahmad recently took time to discuss why generative AI has been such a pervasive trend in data management and analytics, including its assistive and agentive nature as well as its potential for unlocking unstructured data that has long been difficult to operationalize.
In addition, she spoke about other data management and analytics trends and how they are complementing generative AI to advance what enterprises can do with data.
Editor’s note:This Q&A has been lightly edited for clarity and conciseness.
Generative AI has obviously been a major trend over the past couple of years. Is it accurate to say it’s been the top trend in data management and analytics?
Yasmeen Ahmad: One hundred percent. Generative AI has been a massive trend across multiple dimensions. Generative AI is a fundamental technology that is truly transforming the way data platforms are being built, the way data platforms are being used — a lot of enterprise data has been dark — and then generative AI is changing the way that humans are working. It’s transforming their experience. It’s a big trend because it’s so multifaceted and multilayered in the impact it’s having across all these different dimensions.
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Generative AI is a fundamental technology that is truly transforming the way data platforms are being built, the way data platforms are being used … and then generative AI is changing the way that humans are working. Yasmeen AhmadManaging director of strategy and outbound product management for data, analytics and AI, Google
You addressed this in part in your last answer, but to delve a little deeper, what does generative AI enable that makes it such a dominant trend in data and analytics?
Ahmad: Generative AI is a fundamental technology transforming the landscape of data management and analytics in two very important dimensions. First, what we see from organizations is that 80% to 90% of enterprise data today is unstructured. It’s PDFs, documents, images, videos. That is data that has not traditionally been analyzed. We didn’t have the tool set. Generative AI is the tool set to unlock multimodal data that previously was inaccessible. That, in itself, opens up new insights, new use cases that weren’t possible before.
In addition, combining multimodal data with traditional structured data adds to and enhances traditional analytics. Gartner reported that 66% of enterprise data is dark data. Generative AI is eliminating that dark data.
What are some of the use cases you alluded to that weren’t previously possible?
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Ahmad: We have a customer, Symphony Communications, that is using generative AI with call center transcript data. It’s audio data that previously might have been tagged manually to capture some data to do sentiment analysis. Now, with audio transcripts, they can get deep, rich, meaningful insights by analyzing the words. They can generate responses that a call center agent can read to a customer live, in real time. Beyond that, they can get much more nuanced to understand what customers are talking about, what the sentiment is. They have the ability to do translation on the fly. They have all of this rich analysis that wasn’t previously possible. That’s one example.
Another is HCA Healthcare. They’re using Google’s BigQuery and BigLake multimodal data foundation to bring together traditional structured patient data with documents and notes from clinicians and physicians and with image data from X-rays and MRIs. Traditionally, they analyzed the structured data to look for trends in their patient population. What they were not able to do was bring together that rich data you get with physician notes and with images to really do analysis around diagnoses and look at patient healthcare. They’re using generative AI with traditional models to improve healthcare in a way they just weren’t able to before.
Where are enterprises in their generative AI development cycle — are they still in the idea stage or have they moved to the development and production stages?
Ahmad: We are seeing very fast innovation in the generative AI space with customers accelerating through the exploratory phase of pilot testing and proof-of-concepts to getting into pilot production. With many generative AI use cases, we still see a human in the loop — they’re not fully automating the generative AI technology. But they are putting it into the hands of their businesspeople, business users, to drive outcomes. I’ve never before seen this pace of innovation with a new technology.
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What makes that pace of innovation possible?
Ahmad: The key is that generative AI isn’t a new technology where you have to start an entirely new data platform or ecosystem. The way it’s being built is that generative AI models are being integrated into existing data platforms, the ability to run a large language model over existing data. There’s an ability to tap very quickly into low-hanging fruit. Then, as customers are maturing, we’re seeing 600% year-over-year growth in using multimodal data.
There’s a gravitational pull toward bringing more multimodal data sets to expand the use cases they were doing initially. There’s a lot of exploration happening to understand its potential. We’re seeing massive exploration as customers understand how this technology fits into their landscape, how it’s going to transform their business. And today, there’s lots of human-driven generative AI, but we’re already seeing that in the future it’s going to be generative AI assisted by humans.
There’s been a huge amount of buzz around generative AI that’s made it such a big trend in data management and analytics — is it living up to the hype?
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Ahmad: Technologies are typically overestimated in the near term and underestimated in the long term. That analogy absolutely applies to generative AI. There’s massive amounts of hype and energy around what it can do that’s now being broken down to figure out how to get to business results. But the long-term implications of this technology are transformational. I lean into the idea that it is as big as the internet or mobile phones in terms of the transformational impact it can have on so many parts of everyday life for us as humans and consumers and patients, and also for businesses in the way that they operate and meet the needs of those humans, consumers and patients.
As generative AI moves beyond hype and more enterprises develop pilot models, what are they discovering about the reality of generative AI development?
Ahmad: For enterprises, doing initial use cases and getting to insights in pilots has been great. But generative AI is shining a light on the data platform. The challenge is no longer on having an AI technology — generative AI has made that easy. The challenge is how to make sure there’s a trusted AI-ready data foundation. With generative AI, the efficacy of models is linked to data, the quality of high-volume data needed for training, for tuning, for RAG [retrieval-augmented generation].
The No. 1 conversation we’re now having with customers is about making sure their enterprise data is ready, it’s trusted, it’s governed, especially as they bring together multimodal data foundations. They want to govern all that data the same way they governed traditional structured data, so they need a single access control and governance pane across diverse types of data, and they need to easily use that data for LLM training, tuning, RAG and prompting.
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We’ve spoken extensively about generative AI, so what are some other major trends in data management and analytics?
Ahmad: Still related to generative AI are the ideas of assistive and agentic experiences. Data governance and data quality are top concerns. Often, the No. 1 thing C-suite executives talk to me about is data governance and how to trust their data. What we’re seeing is that generative AI can support with that. It can be an assistive technology to understand data drift, finding data anomalies and even building and generating metadata and semantics. And we know semantics are important when training generative AI models because semantics give models context about a business, the language of a business, and help generative AI give more accurate and precise answers.
Traditionally, a human had to build all those semantics and curate all that data and manage the quality. We’re actually applying generative AI to manage that problem because it has the ability to generate semantics by looking at the data, looking at relationships. We see generative AI as a massive accelerator for data engineering teams that had a lot of human toil.
If that’s the assistive nature of generative AI, what is the agentic?
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Ahmad: It’s the notion of data agents that operate on the data analytics lifecycle and transform the experience. Rather than a human coming to data and asking for an insight or for data quality to be improved, a data agent is monitoring data, looking for anomalies, surfacing insights, suggesting semantic modeling metrics to monitor. We’re moving from a reactive world to one where generative AI is proactive in supporting the data analytics lifecycle. The agentic world is supported by the evolution we’re seeing with LLMs.
As we evolve LLMs, it’s not just about the size of the model increasing, the parameter size increasing. Of course that’s improving quality, but at the LLM scale, we’re starting to see emergent capabilities where they’re able to reason much better, understand causality. That leads to LLMs being able to reason and understand if the answers it’s giving are 100% accurate and whether there are nuances to the answers. They’re getting better at evaluating their own answers. That’s what will power a more agentic future where an organization will have data agents that essentially power the enterprise.
What about other data management and analytics trends — what else are you seeing enterprises emphasize?
Ahmad: Two others we’re seeing are real time and automation. When you bring generative AI together with real time and automation, now you can truly deliver the transformation businesses are looking for. With digitalization, businesses were able to get much more data about themselves. Now that we’re in a world where more data is being captured, the next evolution is to use generative AI for intelligence with real time to be able to generate outputs and action them in real time. So, we’re seeing an uptick in streaming. Historically, we were feeding real-time pipelines with aged insights. Now, [enterprises] can run machine learning and LLMs over real-time streams of data and pipeline out real-time actions. There’s a flywheel of getting real-time data in, running generative AI and automating it all. It’s that true transformation that businesses have been waiting for.
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Great innovation comes from bringing together diverse pieces of technology that together create more innovation, and this feels like a moment when pieces of technology are coming together that can drive transformation.
What’s the timeline for converging those technologies to transform business?
Ahmad: We have the entire stack from the foundational technology layer to the LLMs to the data platforms with real-time streaming data. The integrated stack exists today. Over the last two years, we’ve placed a heavy emphasis on unification and simplification because to power this transformation, you need unified platforms and simplified, integrated technology. Google has an open ecosystem, so there are integrations between Google technologies plus integrations with partners. Integration and unification is a key pillar. That foundation is needed to build a transformative world.
Eric Avidon is a senior news writer for TechTarget Editorial and a journalist with more than 25 years of experience. He covers analytics and data management.
OpenAI could undergo massive changes next year, which include getting a brand new logo. According to Fortune, though, staff members were less than enthused when they got a sneak peek of its supposed new logo at a recent company-wide meeting. The company’s hexagonal flower symbol, which has become pretty recognizable thanks to ChatGPT’s popularity, is gone. Instead, it’s replaced by a large black “O” or a simple ring or circle that staffers reportedly found to be devoid of creativity — ominous, even.
Based on how the publication’s sources described it, the new logo sounds like the complete opposite of OpenAI’s current one, which was designed to represent “precision, potential and optimism.” The company apparently started its redesign efforts a year ago after hiring new people for its internal creative and design team. Fortune says one of the reasons OpenAI is going for a brand new look is because it doesn’t own the typefaces used for its logo and its website. The company is, perhaps, looking to solidify its identity as it becomes more of a household name.
Fortune also previously reported that OpenAI is changing its convoluted non-profit corporate structure next year. The company started as a non-profit, and a non-profit entity still controls its for-profit arm. Sam Altman, OpenAI’s CEO, reportedly told employees that the company is moving away from its non-profit structure and is becoming a more traditional for-profit company. If OpenAI’s leaders listen to employee feedback, though, then the new OpenAI will debut with another logo and not one that even its own people find sinister.
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RallyHere is a backend services provider that supports the launch of live services games such as Smite 2 and those coming from ProbablyMonsters.
RallyHere is a backend technology company that makes it easier for game companies to launch multiplayer games. It’s a small team based in Atlanta that made it possible to create the multiplayer gaming in the title Smite. Its focus is on live services games, a new category that promises riches but, as recent events have shown, also raises a lot of challenges.
“You have to be steeled for failure and prepared for success in this industry,” said Stewart Chisam, head of RallyHere, in our interview. “It’s a real tough industry. Most games struggle. But if your game does explode (in a good way), the last thing you want to do is burn that lottery ticket. No one knows how their game is going to do before you launch it. We de-risk it.”
It’s a category of gaming that is full of opportunity and peril, as live services games like Smite have lasted for years while Sony’s recently launched Concord — envisioned to last for years as a live services game — flopped in the market and was canceled after just 12 days in the market. One of ProbablyMonsters‘ former divisions (sold to Sony), Firewalk Studios, made the Concord game with the hopes it would last for years. It didn’t. But ProbablyMonsters has more games in the works, and it has raised $250 million.
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Chisam said in an interview at the Devcom game developer event in Germany that RallyHere’s job is to offload game developers by handling backend services tasks so the game makers can focus on the game. Hi-Rez Studios has created the RallyHere division to provide its technology to other game companies. The idea is to offload mundane yet critical tasks that game developers don’t have to do so they can focus on making a great game, said Chisam.
“We’re plumbing and infrastructure for these games. What’s going to set your game apart is your game not necessarily the plumbing. It will only set your game apart of the plumbing is bad. Strengthening that plumbing is an advantage we have,” Chisam said.
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Chisam said that RallyHere has been crucial in helping its parent company bring Smite 2 to its current stage, just ahead of its launch. It’s a setup not unlike Epic Games and how it uses its game Fortnite to learn about development challenges and address them with improvements to its Unreal game engine. It’s like eating your own dogfood.
“Smite 2 will be interesting. Making a sequel to a live service game is an interesting challenge, but we’re very excited. It’s been great for RallyHere, providing the tech side. And of course, RallyHere is associated with Hi-Rez Studios, which is making Smite 2. It’s good synergy for both learning do a lot of interesting things,” Chisam said.
RallyHere is also accelerating the development of new titles from the Battle Barge and Hidden Grove teams.
Origins
Stewart Chisam, CEO of RallyHere, at Devcom 2024.
Atlanta-based Hi-Rez Studios announced RallyHere in February 2023, and the goal in the first year or so was to find early customers to work with. That plan worked out. Now RallyHere has 40 people.
Chisam believes the lessons learned in working on the Smite titles will be useful to other game companies. The backend solutions paired with an expert engineering support team will help shape the success and longevity of live service games.
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“Live service games like Smite 2 are incredibly complex,” Chisam said in a talk at Devcom. “You’re not just managing a game; you’re managing an entire ecosystem of players, sessions, servers, and data. That’s where our platform comes in.”
This kind of talk has been echoed by a number of other game backend solution companies, like Playfab, which was acquired by Microsoft.
Chisam said his company works with live services game makers before they launch so that they can manage their live services. He said a lot of customers seem to need help with the prototyping phase as well. A live service game has to have a lot of operations in place as it proceeds. The RallyHere team has enough veterans on it to help companies set up community management and support and more.
“In our view, a company like RallyHere is only going to be successful if our customers are successful, and it’s really important to get to get those other operational elements set up well. And we think over time, we’ll learn where there are opportunities to further automate some of those things and integrate them into the software tools,” he said.
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Four key platform components
Chisam highlighted the four key components of RallyHere’s platform, connecting directly to the challenges all multiplatform, cross-progression live service game developers face.
He said the first thing to focus on is player management.
“At the heart of any great game is a strong connection with the players,” Chisam said. Whether it’s handling logins, linking accounts, or managing a player’s inventory and progress, the goal is to ensure players feel invested and enjoy the game without hiccups. It’s about giving developers the tools to engage and retain players over the long haul.
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He also said the next component is sessions and server orchestration. Chisam then introduced Gameflow, explaining, “It’s our comprehensive solution that encompasses Session Management, Matchmaking, and Fleet Commander. Together, they form a powerful system that ensures players are grouped effectively and their sessions are hosted on the best possible servers. This combination balances performance and cost, ensuring that, no matter where your players are, they’re getting the best possible experience.”
RallyHere also focuses on publishing and LiveOps.
“It’s not enough just to launch a game,” Chisam continued. “You’ve got to keep it fresh, keep it engaging. That’s where our Publishing & LiveOps tools come in. These tools help developers manage everything from in-game purchases to rolling out new content and events. And with our Developer Portal, game dev teams can quickly adjust and respond to what’s happening in the game, keeping the community vibrant and the experience fresh.”
And finally RallyHere focuses on data and analytics. Chisam discussed the importance of data in making informed decisions about a game’s future.
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“Our data and analytics tools give developers deep insights into what’s happening in their game. It’s not just about tracking KPIs; it’s about understanding player behavior, seeing what’s working and what’s not, and then making the right decisions to improve the game. Whether fine-tuning gameplay mechanics or identifying the best times to launch new content, the data we provide helps developers make smarter decisions that enhance the player experience.”
A shared vision: RallyHere’s collaboration with ProbablyMonsters
RallyHere’s platform isn’t just powering Smite 2; it’s also driving forward the work at ProbablyMonsters, an independent video game company known for its innovative approach to development. ProbablyMonsters has raised more than $250 million to date.
RallHere’s partnership is built on the same technological foundation that supports Smite 2, providing comprehensive live service operations for ProbablyMonsters’ upcoming titles.
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Mark Subotnick, senior vice president of partnerships at ProbablyMonsters, said in a statement that RallyHere’s track record and deep understanding of game development were key factors in the decision to partner.
“RallyHere isn’t just another service provider,” Subotnick said. “They are also game developers who understand at a deep level what we’re trying to achieve and how to get us there.”
Subotnick emphasized the benefits of working with RallyHere, particularly in terms of reducing the operational headaches that often come with game development. “By having a trusted partner like RallyHere, we can focus on the game itself, knowing that our backend needs are expertly managed,” he added. This close collaboration has enabled ProbablyMonsters to accelerate their development process, moving quickly from testing to playtesting environments with RallyHere’s support.
RallyHere’s growing influence in live service gaming
RallyHere handles live operations for Smite 2.
The success of Smite 2’s alpha launch and the ongoing partnership with ProbablyMonsters highlight RallyHere’s growing influence in the live service gaming space. The platform’s ability to support games at scale, combined with its deep integration with developers, positions RallyHere as one of the games backend services leaders.
As Chisam pointed out at Devcom, the real work begins after a game’s launch. The collaboration between RallyHere and ProbablyMonsters exemplifies the mutual benefits of a well-aligned partnership, with both companies gaining increased velocity and success as they work together to bring new games to market. This partnership sets the stage for future collaborations that will continue to shape the landscape of live service games, Chisam said.
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As Activision noted for Call of Duty, skill-based matchmaking is hard because game makers have to balance getting people into a match fast with putting the right combination of skillful players into the match to make the game close.
“I’d rather wait for minutes rather than get into a bad match,” he said. “If you have smaller numbers of players, the problem gets a lot harder.”
Typically, game companies don’t know what load a game can handle until they have lots of players. They can do testing when there are hundreds or small thousands of layers. But when it comes time to launch, there could be a million players or more ready to play the game. And they won’t want to wait.
Looking ahead
Harold Ryan, former head of Bungie, is CEO of ProbablyMonsters.
RallyHere is working with ProbablyMonsters on a couple of games. Going into 2025, Chisam said, “We’re now looking to more ramp up the sales and marketing and start to execute more on signing up a lot more customers.”
The tech and operations are stable, he said. Now customers with multiple games like ProbablyMonsters can ship them with a common platform. The result is common operations for publishing teams, marketing teams, community and support teams, and common data collection for key metrics.
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“That’s really becoming a focus. We’re working with one other kind of multigame publisher we haven’t announced yet as well,” he said.
One of the tasks is to get players in and out of matches in a smooth game flow. Doing that successfully is a complicated thing to orchestrate, he said. There are multiple vendors in this space.
“What we’re able to do is put one API that developers can develop to and then we’re able to go out and work with all of these vendors, plus the major cloud vendors like Azure, and orchestrate this for you, versus you having vendor lock in to any one of those players,” Chisam said. “If one of the vendors has a problem, we can seamlessly reallocate in the backend to another vendor.”
As far as pricing goes, Chisam said his firm is close to the enterprise subscription pricing of other rivals in the market, and RallyHere’s support for Smite 2 is a good proof point. The RallyHere team has grown to about 40 people. The company is a wholly owned subsidiary of Hi-Rez.
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As for big hits this year like Helldivers 2 and Palworld, Chisam said that if a game is extremely successful like those games, RallyHere can help a company pivot much faster and gain more advantages given the server orchestration and cross-platform work.
Disclosure: Devcom paid my way to Germany, where I moderated a couple of panels.
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Kirsten Korosec, Devin Coldewey, and Rebecca Bellan got back on the mic for the latest episode of Equity to discuss several weird things and at least one cool thing. First, the crew talked about the least weird thing of the week: how nice it is that Cohere co-founder Nick Frosst has a band that people really like.
Then we got weirder. First the good weird: a helmet that squeezes your head, but for a really good reason. It prevents hair loss from chemotherapy. Devin covered Luminate’s latest fundraise and news, and everyone was pleased that money was going to a startup that may really be helping people feel better about themselves during a difficult time. The company is hoping to improve at-home care as well.
Next, Kirsten explained the weird phenomenon of Flink, the “quick commerce” startup that just recently was rumored to be on the block for about $106 million, instead raising $115 million. Quite a turnaround! But as the team discusses, it may be that investors see the possibility that the “tumultuous time” for this sector is ending and Flink may have a good grip on the German market. Still…
Then the weirdness begins in earnest. Rebecca is at the “Principled Business Summit,” aimed at “reclaiming capitalism” from, apparently, itself. She is getting mixed messages from the crowd and the content, which seems to combine enthusiasm for doing the right thing with some fringe tendencies to do… other things.
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And weirdest of all, autonomous trucking startup TuSimple’s pivot to… AI-generated animation and video games. What?! Though there is some overlap between simulation and animation/gaming, it’s a wild and unexpected change for the company, and a lot of shareholders are not going for it. Apparently the new division is working on another adaptation of “The Three-Body Problem,” so that’s good… but what about the $450 million they were going to spend on trucks? That conflict is playing out before our eyes.
Equity is TechCrunch’s flagship podcast, produced by Theresa Loconsolo, and posts every Wednesday and Friday.
Subscribe to us on Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod. For the full episode transcript, for those who prefer reading over listening, check out our full archive of episodes over at Simplecast.
The (digital) ink has barely dried on our iPhone 16 review, and we’re already into iPhone 17 rumor season – with one reliable source suggesting that there are display upgrades in store when Apple‘s 2025 refresh rolls around.
This comes from well-known industry analyst Ross Young (via 9to5Mac), who says that the two cheaper iPhone 17 models are going to get the same always-on display and ProMotion tech that has previously been exclusive to the Pro and Pro Max handsets.
That means an upgrade to the LTPO (low-temperature polycrystalline oxide) screen technology required to reduce power consumption and support a variable refresh rate, all the way up to 120Hz (or all the way down to 1Hz) when required.
However, while Young initially predicted Face ID would be embedded in the display on the iPhone 17 Pro and iPhone 17 Pro Max, he later said that was a misunderstanding – so we’ll have to wait a little while longer for developments in that department.
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Pro vs non-Pro
The iPhone 16 Pro, with ProMotion (Image credit: Future / Lance Ulanoff)
If the less expensive iPhone 17 models do indeed get LTPO display technology next year, there will be less of a distinction between these variants and the Pro and Pro Max – though the latter handsets may well still get better cameras and faster processors.
It also links in with another rumor we’ve heard about next year’s iPhone refresh: that the iPhone 16 Plus will be replaced not by another Plus model, but by an iPhone 17 Air – perhaps with a slimmer, more stylish design at the same price point.
Apple has of course already used the same branding with the iPad Air and the MacBook Air, so it wouldn’t be a huge surprise if the moniker was added to one of the iPhone 17 models as well. However, we’ll need to wait almost another 12 months to be sure.
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This isn’t the only iPhone 17 rumor that’s emerged already, either: there has also been talk that the 2025 iPhones are going to get improved selfie cameras and a bump in the RAM, alongside the usual boost in performance.
Yasmeen Ahmad
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