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Apple M2 Pro and Max Chips Repeat a Successful Upgrade Strategy

First the M2. Now we’ve got the M2 Pro and M2 Max. Maybe we’ll see an M2 Ultra processor powering Apple Mac Pro computers in the coming months.

With its M2 Pro and M2 Max processors, Apple is repeating a strategy that worked well for its earlier M1 designs. By grafting some extra circuitry onto an efficient chip foundation, Apple can offer a significant upgrade to its new M2-based MacBook Pro laptops without a full chip overhaul.

Apple introduced its first in-house Mac processor, the M1, for MacBook Air laptops that arrived in 2020. The M1 already took advantage of chip design work for the iPhone’s A-series chips, but Apple beefed up the M1 with more processing cores to make the M1 Pro and M1 Max in late 2021 for higher-end MacBook Pro laptops. Then, in 2022, it glued two M1 Max chips together into the top-end M1 Ultra.

Now, Apple is headed the same route with the M2, which debuted in 2022 and now is joined by the M2 Pro and M2 Max for new MacBook Pro models. If history continues to repeat itself, we could see a Mac Pro based on a hulking M2 Ultra processor in the coming months.

The chips’ speed boost over M1 equivalents that debuted 15 months ago is significant — 20% at least by Apple’s measurements. Owners of year-old M1-generation MacBook Pro laptops to upgrade. But for those using older Macs based on the older Intel chips Apple ejected from its product line, the speed boost and better battery life could be much more compelling.

«These new Macs should help entice moving off Intel to M series in 23,» Creative Strategies analyst Ben Bajarin said in a tweet Tuesday. His firm estimates 42% of Mac owners in the US are still using Intel-based models, and the fraction is probably higher worldwide.

Apple didn’t respond to requests for comment. Intel declined to comment.

How did Apple speed up the M2 Pro and M2 Max chips?

The M2 Pro and Max chips are faster thanks to new designs for the chip’s central processing unit cores for general computation and graphics processing unit cores for handling graphics tasks and some other jobs that work on GPUs. The new designs also have more CPUs, GPUs and another core type for accelerating artificial intelligence tasks, which Apple calls its Neural Engine.

The M1 Pro has eight or 10 CPU cores, depending on configuration, and the M1 Max has 10. The M2 Pro has 10 or 12, and the M2 Max has 12. The M2 generation is 20% faster, Apple said, citing unspecified but industry standard speed tests.

CPU performance is the foundation of everything a processor does, and all the M-series Pro and Max models employ four power-efficient CPU cores for better battery life. The remaining CPU cores offer higher performance cores for more important work. Intel also has adopted this approach, pioneered for smartphones.

For GPUs, used for tasks like playing games and editing photos and videos, the M1 Pro came with 14 or 16 cores and the M1 Max with 16 to 32 cores. The M2 Pro boosts that to 16 or 19 GPU cores, and the M2 Max to 30 or 38. The M2 GPU performance is 30% faster, though part of the speed boost comes from better cache memory on the chip, Apple said.

The neural engine has 16 cores on both M1 and M2 generations, but Apple boasts its AI performance is 40% faster with the new chips. AI software is just getting started, but it’s used in important jobs like some Adobe Photoshop image editing, and you can expect that AI performance to become more and more important as more developers figure it out.

Speed boosts compared to Intel-based Macs, which use years-old Intel chips, are more notable. The M2 Pro is 2.5 times faster at compiling software and 80% faster at Photoshop image editing compared with an older 16-inch MacBook with an Intel i9 processor, Apple said. As for the M2 Max, it’s twice fast at video color adjustments and six times faster at Da Vinci Resolve video editing.

Some of the speed boost on the M2 Max comes from faster memory transfer, doubling to 400 megabytes per second, which helps with data-heavy chores like video editing and 3D modeling. The M2 Max new models also accommodate up to 96GB of memory, up from 64GB on the M1 Max.

We won’t see third-party speed tests until MacBook Pro reviews with the M2 Pro and Max processors arrive. CNET editor Dan Ackerman gave the M2-based MacBook Air an editor’s choice accolade, citing its «excellent performance and battery life.»

That model came with a $200 price increase over its predecessor, though, and the M2-generation MacBook Pro laptops aren’t cheap, either. The model with a 14-inch screen and lowest-end 10-core M2 Pro costs $1,999; with a 12-core M2 Max and other improvements, the price increases to $3,099. The 16-inch models start at $2,499 but rise to $3,499 with an M2 Max processor and more storage capacity.

How are the M2 Pro and M2 Max chips built?

As with all Apple-designed processors for the last few years, Taiwan Semiconductor Manufacturing Co. (TSMC) builds the chips.

As with the M2, the M2 Pro and Max are built with a second-generation 5-nanometer manufacturing process. (A nanometer is a billionth of a meter, and chip manufacturing processes with lower nanometers refer to more advanced manufacturing processes. However, for years now, the numbers have been mere labels of convenience, not actual measurements signifying actual miniaturization progress.)

New manufacturing processes shrink chips’ fundamental electronic elements, called transistors, although that miniaturization is harder these days. That permits more circuitry on a chip. The transistor tally increased from 33.7 billion in the M1 Pro to 40 billion in the M2 Pro; the Max models increased from 57 billion to 67 billion.

TSMC has begun mass product manufacturing on a newer 3 nanometer (3nm) process. Expect that to be used for future iPhone, iPad and Mac processors, a move that should permit even more transistors.

Technologies

Google races to put Gemini at the center of Android before Apple’s AI reboot

Google is using its latest Android rollout to position Gemini as the AI layer across phones, Chrome, laptops and cars.

Google is using its latest Android rollout to make Gemini less of a chatbot and more of an operating layer across the phone, browser, car and laptop, just weeks before Apple is expected to show its own Gemini-powered Apple Intelligence reboot at WWDC.
Ahead of its Google I/O developer conference next week, the company previewed a number of Android updates, including AI-powered app automation, a smarter version of Chrome on Android, new tools for creators, a redesigned Android Auto experience, and a sweeping set of new security features.
Alphabet is counting on Gemini to help Google compete directly with OpenAI and Anthropic in the market for artificial intelligence models and services, while also serving as the AI backbone across its expansive portfolio of products, including Android. Meanwhile, Gemini is powering part of Apple’s new AI strategy, giving Google a role in the iPhone maker’s reset even as it races to prove its own version of personal AI on the phone is further along.
Sameer Samat, who oversees Google’s Android ecosystem, told CNBC that Google is rebuilding parts of Android around Gemini Intelligence to help users complete everyday tasks more easily.
“We’re transitioning from an operating system to an intelligence system,” he said.
As part of Tuesday’s announcements. Google said Gemini Intelligence will be able to move across apps, understand what’s on the screen and complete tasks that would normally require a user to jump between multiple services. That means Android is moving beyond the traditional assistant model, where users ask a question and get an answer, and acting more like an agent.
For instance, Google says Gemini can pull relevant information from Gmail, build shopping carts and book reservations. Samat gave the example of asking Gemini to look at the guest list for a barbecue, build a menu, add ingredients to an Instacart list and return for approval before checkout.
A big concern surrounding agentic AI involves software taking action on a user’s behalf without permissions. Samat said Gemini will come back to the user before completing a transaction, adding, “the human is always in the loop.”
Four months after announcing its Gemini deal with Google, Apple is under pressure to show a more capable version of Apple Intelligence, which has been a relative laggard on the market. Apple has long framed privacy, hardware integration and control of the user experience as its advantages.
Google’s Android push is designed to show it can bring AI deeper into the device experience while still giving users control over what Gemini can see, where it can act and when it needs confirmation.
The app automation features will roll out in waves, starting with the latest Samsung Galaxy and Google Pixel phones this summer, before expanding across more Android devices, including watches, cars, glasses and laptops later this year.
The company is also redesigning Android Auto around Gemini, turning the car into another major surface for its assistant. Android Auto is in more than 250 million cars, and Google says the new release includes its biggest maps update in a decade and Gemini-powered help with tasks like ordering dinner while driving.
Alphabet’s AI strategy has been embraced by Wall Street, which has pushed the company’s stock price up more than 140% in the past year, compared to Apple’s roughly 40% gain. Investors now want to see how Gemini can become more central to the products people use every day.
WATCH: Alphabet briefly tops Nvidia after report of $200 billion Anthropic cloud deal

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Waymo recalls 3,800 robotaxis after glitch allowed some vehicles to ‘drive into standing water’

Waymo issued a voluntary recall of about 3,800 of its robotaxis to fix software issues that could allow them to drive into flooded roadways.

Waymo is recalling about 3,800 robotaxis in the U.S. to fix software issues that could allow them to “drive onto a flooded roadway,” according to a letter on the National Highway Traffic Safety Administration’s website.
The voluntary recall is for Waymo vehicles that use the company’s fifth and sixth generation automated driving systems (or ADS), the U.S. auto safety regulator said in the letter posted Tuesday.
Waymo autonomous vehicles in Austin, Texas, were seen on camera driving onto a flooded street and stalling, requiring other drivers to navigate around them. It’s the latest example of a safety-related issue for the Alphabet-owned AV unit that’s rapidly bolstering its fleet of vehicles and entering new U.S. markets.
Waymo has drawn criticism for its vehicles failing to yield to school buses in Austin, and for the performance of its vehicles during widespread power outages in San Francisco in December, when robotaxis halted in traffic, causing gridlock.
The company said in a statement on Tuesday that it’s “identified an area of improvement regarding untraversable flooded lanes specific to higher-speed roadways,” and opted to file a “voluntary software recall” with the NHTSA.
“Waymo provides over half a million trips every week in some of the most challenging driving environments across the U.S., and safety is our primary priority,” the company said.
Waymo added that it’s working on “additional software safeguards” and has put “mitigations” in place, limiting where its robotaxis operate during extreme weather, so that they avoid “areas where flash flooding might occur” in periods of intense rain.
WATCH: Waymo launches new autonomous system in Chinese-made vehicle

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Qualcomm tumbles 13% as semiconductor stocks retreat from historic AI-fueled surge

Semiconductor equities reversed sharply after a broad AI-driven advance, with Qualcomm suffering its worst day since 2020 amid inflation concerns and rising oil prices.

Semiconductor stocks fell sharply on Tuesday, reversing course after an extensive rally that had expanded the artificial intelligence investment theme well past Nvidia and driven the industry to unprecedented levels.

Qualcomm plunged 13% and was on track for its steepest single-day decline since 2020. Intel shed 8%, while On Semiconductor and Skyworks Solutions each lost more than 6%. The iShares Semiconductor ETF, which benchmarks the overall sector, fell 5%.

The sell-off came after a key gauge of consumer prices came in above forecasts, and as conflict in Iran pushed crude oil higher—prompting investors to shift away from riskier assets.

The preceding advance had widened the AI opportunity set beyond longtime industry leader Nvidia, which for much of the past several years had largely carried the market to new peaks on its own.

Explosive appetite for central processing units, along with the graphics processing units that power large language models, has sent chipmakers to all-time highs.

Market participants are wagering that the shift from AI model training to autonomous agents will lift demand for additional AI hardware. Among the beneficiaries are memory chip producers, which are raising prices as supply remains tight.

Micron Technology slid 6%, and Sandisk cratered 8%. Sandisk’s stock has surged more than six times over since January.

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