
Apple investors seek clarity on tariffs, AI strategy as iPhone sales decline
Company's AI strategy seen as conservative, lagging Android competitors
Tariff threats may lead to higher costs, analysts warn
Apple stock down 16% year to date
April 29 (Reuters) - Apple is expected to face a string of questions over the delayed roll-out of key AI features and the impact of the Sino-U.S. tariff standoff on its business, when it reports results on Thursday.
Even as Apple benefited from a rush of orders for its recently launched lower-priced iPhone 16e in the January-March period ahead of potential tariffs, Wall Street analysts still expect the company will report a small fall in iPhone sales. That would mark a second straight quarter of declines.
The Trump administration has so far spared electronics from tariffs, but Washington has signaled that some levies could come in the coming weeks. The uncertainty has sent shares of Apple, which makes 90% of its products in China, down more than 16% this year, and wiping off over $600 billion from its market value.
Apple will try to mitigate tariffs by shifting production of U.S.-bound iPhones to India, Reuters has reported. Analysts expect the company to spread some of the tariff costs through its supply chain, while keeping price increases to a minimum to avoid losing market share.
"Tariffs are a sword of Damocles for Apple – dangling, disruptive and politically charged," said Eric Schiffer, chairman of Patriarch Organization, a California-based private equity firm that holds Apple shares.
Unlike rivals such as Samsung and Alphabet's Google, Apple has also been slow to roll out some important AI features it promised last year at its developer conference.
Improvements to voice assistant Siri, a common ask from users and investors, have been delayed to 2026, and Apple pulled a commercial that promoted AI functionalities that were not yet available.
AI features are especially important in China, where Apple has been losing market share to domestic rivals such as Huawei. Apple has partnered with Alibaba to offer AI services in China but hasn't offered a timeline for their roll-out.
IPhone shipments in China fell 9% in the March quarter, the only major smartphone maker to post a decline in the region, according to data from research firm IDC.
Despite these challenges, strong demand for the $599 iPhone 16e in India helped Apple take the top spot for global smartphone sales in the quarter, according to Counterpoint Research.
Apple's cautious, privacy-first approach to AI deployment has slowed its roll-out and left the company playing catch up, said Jacob Bourne, analyst at eMarketer.
"With tariffs threatening cost structures, Apple faces pressure to move faster on AI innovation and supply chain realignment - both of which are capital intensive".
Overall, Apple's revenue is expected to rise 4.2% in the January-March period, its fiscal second quarter, roughly matching the pace in the first quarter. Growth will likely be driven by upbeat iPad demand and growth in the services business.
IPad sales are expected to rise 9.1% in the second quarter, while the services business, Apple's biggest revenue generator after the iPhone, will likely grow 11.8%.
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Indian Express
12 minutes ago
- Indian Express
Apple researchers show how popular AI models ‘collapse' at complex problems
A new research paper by a group of people at Apple has said that artificial intelligence (AI) 'reasoning' is not all that it is cracked up to be. Through an analysis of some of the most popular large reasoning models in the market, the paper showed that their accuracy faces a 'complete collapse' beyond a certain complexity threshold. The researchers put to the test models like OpenAI o3-mini (medium and high configurations), DeepSeek-R1, DeepSeek-R1-Qwen-32B, and Claude-3.7- Sonnet (thinking). Their findings showed that the AI industry may be grossly overstating these models' capabilities. They also benchmarked these large reasoning models (LRMs) with large language models (LLMs) with no reasoning capabilities, and found that in some cases, the latter outperformed the former. 'In simpler problems, reasoning models often identify correct solutions early but inefficiently continue exploring incorrect alternatives — an 'overthinking' phenomenon. At moderate complexity, correct solutions emerge only after extensive exploration of incorrect paths. Beyond a certain complexity threshold, models completely fail to find correct solutions,' the paper said, adding that this 'indicates LRMs possess limited self-correction capabilities that, while valuable, reveal fundamental inefficiencies and clear scaling limitations'. For semantics, LLMs are AI models trained on vast text data to generate human-like language, especially in tasks such as translation and content creation. LRMs prioritise logical reasoning and problem-solving, focusing on tasks requiring analysis, like math or coding. LLMs emphasise language fluency, while LRMs focus on structured reasoning. To be sure, the paper's findings are a dampener on the promise of large reasoning models, which many have touted as a frontier breakthrough to understand and assist humans in solving complex problems, in sectors such as health and science. Apple researchers evaluated reasoning capabilities of LRMs through four controllable puzzle environments, which allowed them fine-grained control over complexity and rigorous evaluation of reasoning: Tower of Hanoi: It involves moving n disks between three pegs following specific rules, with complexity determined by the number of disks. Checker Jumping: This requires swapping red and blue checkers on a one-dimensional board, with complexity scaled by the number of checkers. River Crossing: This is a constraint satisfaction puzzle where and actors and n agents must cross a river, controlled by the number of actor/agent pairs and boat capacity. Blocks World: Focuses on rearranging blocks into a target configuration, with complexity managed by the number of blocks. 'Most of our experiments are conducted on reasoning models and their non-thinking counterparts, such as Claude 3.7 Sonnet (thinking/non-thinking) and DeepSeek-R1/V3. We chose these models because they allow access to the thinking tokens, unlike models such as OpenAI's o-series. For experiments focused solely on final accuracy, we also report results on the o-series models,' the researchers said. The researchers found that as problem complexity increased, the accuracy of reasoning models progressively declined. Eventually, their performance reached a complete collapse (zero accuracy) beyond a specific, model-dependent complexity threshold. Initially, reasoning models increased their thinking tokens proportionally with problem complexity. This indicates that they exerted more reasoning effort for more difficult problems. However, upon approaching a critical threshold (which closely corresponded to their accuracy collapse point), these models counter-intuitively began to reduce their reasoning effort (measured by inference-time tokens), despite the increasing problem difficulty. Their work also found that in cases where problem complexity is low, non-thinking models (LLMs) were capable to obtain performance comparable to, or even better than thinking models with more token-efficient inference. With medium complexity, the advantage of reasoning models capable of generating long chain-of-thought began to manifest, and the performance gap between LLMs and LRMs increased. But, where problem complexity is higher, the performance of both models collapsed to zero. 'Results show that while thinking models delay this collapse, they also ultimately encounter the same fundamental limitations as their non-thinking counterparts,' the paper said. It is worth noting though that the researchers have acknowledged their work could have limitations: 'While our puzzle environments enable controlled experimentation with fine-grained control over problem complexity, they represent a narrow slice of reasoning tasks and may not capture the diversity of real-world or knowledge-intensive reasoning problems.' Soumyarendra Barik is Special Correspondent with The Indian Express and reports on the intersection of technology, policy and society. With over five years of newsroom experience, he has reported on issues of gig workers' rights, privacy, India's prevalent digital divide and a range of other policy interventions that impact big tech companies. He once also tailed a food delivery worker for over 12 hours to quantify the amount of money they make, and the pain they go through while doing so. In his free time, he likes to nerd about watches, Formula 1 and football. ... Read More

Mint
16 minutes ago
- Mint
Tata Sons' FY25 revenue is likely to be lower despite record dividends
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New Indian Express
19 minutes ago
- New Indian Express
Apple unveils software redesign while reeling from AI missteps, tech upheaval and Trump's trade war
CUPERTINO (California): After stumbling out of the starting gate in Big Tech's pivotal race to capitalize on artificial intelligence, Apple tried to regain its footing Monday during an annual developers conference that focused mostly on incremental advances and cosmetic changes in its technology. The presummer rite, which attracted thousands of developers from nearly 60 countries to Apple's Silicon Valley headquarters, subdued compared with the feverish anticipation that surrounded the event in the last two years. Apple highlighted plans for more AI tools designed to simplify people's lives and make its products even more intuitive. It also provided an early glimpse at the biggest redesign of its iPhone software in a decade. In doing so, Apple executives refrained from issuing bold promises of breakthroughs that punctuated recent conferences, prompting CFRA analyst Angelo Zino to deride the event as a "dud" in a research note. More AI, but what about Siri? In 2023, Apple unveiled a mixed-reality headset that has been little more than a niche product, and last year WWDC trumpeted its first major foray into the AI craze with an array of new features highlighted by the promise of a smarter and more versatile version of its virtual assistant, Siri — a goal that has yet to be realized. "This work needed more time to reach our high-quality bar," Craig Federighi, Apple's top software executive, said Monday at the outset of the conference. The company didn't provide a precise timetable for when Siri's AI upgrade will be finished but indicated it won't happen until next year at the earliest. "The silence surrounding Siri was deafening," said Forrester Research analyst Dipanjan Chatterjee said. "No amount of text corrections or cute emojis can fill the yawning void of an intuitive, interactive AI experience that we know Siri will be capable of when ready. We just don't know when that will happen. The end of the Siri runway is coming up fast, and Apple needs to lift off." Is Apple, with its 'liquid glass,' still a trendsetter? The showcase unfolded amid nagging questions about whether Apple has lost some of the mystique and innovative drive that has made it a tech trendsetter during its nearly 50-year history. Instead of making a big splash as it did with the Vision Pro headset and its AI suite, Apple took a mostly low-key approach that emphasized its effort to spruce up the look of its software with a new design called "Liquid Glass" while also unveiling a new hub for its video games and new features like a "Workout Buddy" to help manage physical fitness. Apple executives promised to make its software more compatible with the increasingly sophisticated computer chips that have been powering its products while also making it easier to toggle between the iPhone, iPad, and Mac. "Our product experience has become even more seamless and enjoyable," Apple CEO Tim Cook told the crowd as the 90-minute showcase wrapped up. IDC analyst Francisco Jeronimo said Apple seemed to be largely using Monday's conference to demonstrate the company still has a blueprint for success in AI, even if it's going to take longer to realize the vision that was presented a year ago. "This year's event was not about disruptive innovation, but rather careful calibration, platform refinement and developer enablement —positioning itself for future moves rather than unveiling game-changing technologies," Jeronimo said. Apple's next operating system will be iOS 26 Besides redesigning its software. Apple will switch to a method that automakers have used to telegraph their latest car models by linking them to the year after they first arrive at dealerships. That means the next version of the iPhone operating system due out this autumn will be known as iOS 26 instead of iOS 19 — as it would be under the previous naming approach that has been used since the device's 2007 debut. The iOS 26 upgrade is expected to be released in September around the same time Apple traditionally rolls out the next iPhone models. Playing catchup in AI Apple opened the proceedings with a short video clip featuring Federighi speeding around a track in a Formula 1 race car. Although it was meant to promote the June 27 release of the Apple film, "F1" starring Brad Pitt, the segment could also be viewed as an unintentional analogy to the company's attempt to catch up to the rest of the pack in AI technology. While some of the new AI tricks compatible with the latest iPhones began rolling out late last year as part of free software updates, the delays in a souped-up Siri became so glaring that the chastened company stopped promoting it in its marketing campaigns earlier this year.