Amazon has a great deal running now on the M2 MacBook Air, where you can get the slimline laptop for just $700. The main deal price is $849, which is nice at 15 percent off the regular cost. But you can also apply a coupon to the space gray model for an additional discount, bringing the price down even further. For now, you can also nab the silver and starlight colors for $700 without adding in a coupon.

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$700 at Amazon

This is the 2022 model of the MacBook Air, and it’s some of the best we’ve seen out of Apple laptops. The M2 chip is a big factor in what takes this laptop from a lightweight to a powerhouse. By using Apple’s own silicon, the computer reaches pretty high standards in performance, with 10 GPU cores and a 35 percent boost to the speeds of the previous M1 chip. It’s also got a gorgeous Liquid Retina display. The model currently on sale has 8GB RAM and 256GB of solid state drive storage. And once Apple Intelligence starts rolling out next week, the M2 Air is prepared to handle the extra workload of those AI-driven tasks.

The Air is also Engadget’s pick for your best budget Apple laptop. In other words, this is a good deal on the model that’s already a good deal. It’s very possible that Amazon’s supply will be snapped up quickly, so if this catches your eye, we suggest you act fast.

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Noam Brown, a leading research scientist at OpenAI, took the stage at the TED AI conference in San Francisco on Tuesday to deliver a powerful speech on the future of artificial intelligence, with a particular focus on OpenAI’s new o1 model and its potential to transform industries through strategic reasoning, advanced coding, and scientific research. Brown, who has previously driven breakthroughs in AI systems like Libratus, the poker-playing AI, and CICERO, which mastered the game of Diplomacy, now envisions a future where AI isn’t just a tool, but a core engine of innovation and decision-making across sectors.

“The incredible progress in AI over the past five years can be summarized in one word: scale,” Brown began, addressing a captivated audience of developers, investors, and industry leaders. “Yes, there have been uplink advances, but the frontier models of today are still based on the same transformer architecture that was introduced in 2017. The main difference is the scale of the data and the compute that goes into it.”

Brown, a central figure in OpenAI’s research endeavors, was quick to emphasize that while scaling models has been a critical factor in AI’s progress, it’s time for a paradigm shift. He pointed to the need for AI to move beyond sheer data processing and into what he referred to as “system two thinking”—a slower, more deliberate form of reasoning that mirrors how humans approach complex problems.

The psychology behind AI’s next big leap: Understanding system two thinking

To underscore this point, Brown shared a story from his PhD days when he was working on Libratus, the poker-playing AI that famously defeated top human players in 2017.

“It turned out that having a bot think for just 20 seconds in a hand of poker got the same boosting performance as scaling up the model by 100,000x and training it for 100,000 times longer,” Brown said. “When I got this result, I literally thought this broke everything. For the first three years of my PhD, I had managed to scale up these models by 100x. I was proud of that work. I had written multiple papers on how to do that scaling, but I knew pretty quickly that all that would be a footnote compared to this scaling up system two thinking.”

Brown’s presentation introduced system two thinking as the solution to the limitations of traditional scaling. Popularized by psychologist Daniel Kahneman in the book Thinking, Fast and Slow, system two thinking refers to a slower, more deliberate mode of thought that humans use for solving complex problems. Brown believes incorporating this approach into AI models could lead to major performance gains without requiring exponentially more data or computing power.

He recounted that allowing Libratus to think for 20 seconds before making decisions had a profound effect, equating it to scaling the model by 100,000x. “The results blew me away,” Brown said, illustrating how businesses could achieve better outcomes with fewer resources by focusing on system two thinking.

Inside OpenAI’s o1: The revolutionary model that takes time to think

Brown’s talk comes shortly after the release of OpenAI’s o1 series models, which introduce system two thinking into AI. Launched in September 2024, these models are designed to process information more carefully than their predecessors, making them ideal for complex tasks in fields like scientific research, coding, and strategic decision-making.

“We’re no longer constrained to just scaling up the system one training. Now we can scale up the system two thinking as well, and the beautiful thing about scaling up in this direction is that it’s largely untapped,” Brown explained. “This isn’t a revolution that’s 10 years away or even two years away. It’s a revolution that’s happening now.”

The o1 models have already demonstrated strong performance in various benchmarks. For instance, in a qualifying exam for the International Mathematics Olympiad, the o1 model achieved an 83% accuracy rate—a significant leap from the 13% scored by OpenAI’s GPT-4o. Brown noted that the ability to reason through complex mathematical formulas and scientific data makes the o1 model especially valuable for industries that rely on data-driven decision-making.

The business case for slower AI: Why patience pays off in enterprise solutions

For businesses, OpenAI’s o1 model offers benefits beyond academic performance. Brown emphasized that scaling system two thinking could improve decision-making processes in industries like healthcare, energy, and finance. He used cancer treatment as an example, asking the audience, “Raise your hand if you would be willing to pay more than $1 for a new cancer treatment… How about $1,000? How about a million dollars?”

Brown suggested that the o1 model could help researchers speed up data collection and analysis, allowing them to focus on interpreting results and generating new hypotheses. In energy, he noted that the model could accelerate the development of more efficient solar panels, potentially leading to breakthroughs in renewable energy.

He acknowledged the skepticism about slower AI models. “When I mention this to people, a frequent response that I get is that people might not be willing to wait around for a few minutes to get a response, or pay a few dollars to get an answer to the question,” he said. But for the most important problems, he argued, that cost is well worth it.

Silicon Valley’s new AI race: Why processing power isn’t everything

OpenAI’s shift toward system two thinking could reshape the competitive landscape for AI, especially in enterprise applications. While most current models are optimized for speed, the deliberate reasoning process behind o1 could offer businesses more accurate insights, particularly in industries like finance and healthcare.

In the tech sector, where companies like Google and Meta are heavily investing in AI, OpenAI’s focus on deep reasoning sets it apart. Google’s Gemini AI, for instance, is optimized for multimodal tasks, but it remains to be seen how it will compare to OpenAI’s models in terms of problem-solving capabilities.

That said, the cost of implementing o1 could limit its widespread adoption. The model is slower and more expensive to run than previous versions. Reports indicate that the o1-preview model costs $15 per million input tokens and $60 per million output tokens, far more than GPT-4o. Still, for enterprises that need high-accuracy outputs, the investment may be worthwhile.

As Brown concluded his talk, he emphasized that AI development is at a critical juncture: “Now we have a new parameter, one where we can scale up system two thinking as well — and we are just at the very beginning of scaling up in this direction.”

Last week, police surveillance startup Flock Safety announced that it had bought drone startup Aerodome. The acquisition price was over $300 million, according to sources in the venture world. The number has not been previously reported. 

Both Flock Safety and Aerodome are backed by Andreessen Horowitz and have raised over $680 million and $28 million, respectively, according to PitchBook. Rahul Sidhu, a former police officer, founded Aerodome just 17 months ago, declaring it an “American Dynamism speed-run,” in reference to the name of a16z’s defense tech-focused initiative.  

Sidhu also said the deal was “one of largest tech acquisitions” in public safety history. “Our acquisition isn’t the end of Aerodome, but the beginning of a golden era in public safety tech advancement,” he wrote. 

Aerodome created technology that powers drones as first responders. Right now, many police drone programs require a human to pilot the drone, but drone companies like Skydio, Brinc Drones, and Aerodome are all trying to perfect an autonomous service. For example, when the police receive a 911 call, a drone could take off on its own and scope out the scene, informing police if the area is safe to enter.  

Flock Safety has also zeroed in on law enforcement as a customer, building out cameras that can identify license plates and sensors that detect gunshots. 

The acquisition accelerates Flock Safety’s aggressive expansion into police drones. Flock Safety announced it will be releasing its own drones over the next year and, according to Sidhu’s post, will be hiring an additional 100 engineers for the company’s aviation team. 

The drone expansion plan puts the company in direct competition with drone manufacturer Skydio, which is yet another a16z portfolio company. 

Garrett Langley, founder and CEO of Flock Safety, said the expansion into drones is a no-brainer. “Anyone who’s seen a drone-as-first-responder program in action knows that this technology will play a central role in the future of public safety,” he said in a company blog post. “No other technology helps law enforcement officers get eyes on the scene faster than a drone.” 

Apple plans to release MacBook Airs with M4 chips in early 2025, Bloomberg’s Mark Gurman reports. The company just refreshed the lineup with M3 chips this spring, but the M4 update will “likely” launch between January and March 2025, Gurman says. Both the 13-inch and 15-inch models will apparently get the M4 update, and they’ll have a similar design to the M2 MacBook Air.

The potential spring launch for M4-equipped MacBook Airs means that product line won’t be part Apple’s rumored announcements for next week. With those updates, Apple is going to reveal new MacBook Pros, Mac Minis, and iMacs, Gurman says.

If you’re waiting for a new Mac Studio, though, don’t expect that imminently. The Mac Studio is currently powered by the M2 Max and M2 Ultra chips, but an M4-equipped version is now likely to arrive “after a March software release,” meaning it could happen sometime between March and June, Gurman says. Apple is also apparently working on an M4 Mac Pro, Gurman didn’t give a timeline for when that might come out.

In the spring, Gurman reports that Apple is also aiming to reveal a new iPhone SE, new iPad Airs, “upgraded” iPad keyboards, and new entry-level iPads. The company just released a seventh-generation iPad Mini and is set to launch the first phase of Apple Intelligence features next week.

It’s no secret that 2024’s batch of AI PCs owes much of their success to the excellent batch of Qualcomm Snapdragon chips, which has the best version of Windows Arm running as the OS. However, a nasty split between the two could jeopardize everything, especially for consumers.

According to a breaking news report from Bloomberg, Arm canceled a “license that allowed longtime partner Qualcomm Inc. to use Arm intellectual property to design chips.” The company issued Qualcomm a 60-day notice of the cancellation of said license as required by law. The report stated that the split was caused by a breach of contract back in 2022, which escalated a legal dispute over vital smartphone technology.

The National Space Commission recently approved its fifth lunar mission, called the Lunar Polar Exploration Mission (LUPEX). Unlike the Chandrayaan 1 to 4 missions, this upcoming LUPEX mission is a collaboration between India and Japan. However, it remains part of India’s broader lunar mission series, which aims to eventually send an Indian astronaut to the Moon and bring them back safely. It’s important to note that no astronauts will be sent as part of the LUPEX mission itself. The Union Cabinet had approved the Chandrayaan-4 mission on September 18, and the LUPEX mission is expected to be presented for cabinet approval soon.

Although ISRO and Japan’s space agency JAXA signed an agreement in 2017, progress on the Lupex mission was delayed after India’s Chandrayaan-2 was unable to successfully demonstrate a soft landing on the lunar surface. The LUPEX project is designed to explore the Moon in search of water and other valuable resources. It also aims to develop skills and knowledge in studying the lunar surface. The LUPEX project is a joint international effort, where Japan’s space agency (JAXA) is building the lunar rover, and India’s space agency (ISRO) is creating the lander that will transport the rover to the Moon.

Other space agencies will also send scientific instruments for the mission. NASA’s Neutron Spectrometer will search for hydrogen up to 1 metre (3.3 feet) below the surface at the Moon’s south pole. Meanwhile, the European Space Agency’s (ESA) Exospheric Mass Spectrometer will measure gas pressure and identify chemical signatures on the surface.

Interestingly, the global interest in the Moon is growing and that has been highlighted by the Artemis mission, a US-led initiative aimed at sending astronauts back to the Moon. The goal is to establish a long-term presence on the lunar surface and carry out ongoing exploration activities.

“Recent studies of different observation data suggest that water might exist in the lunar polar regions. These regions are located near the Moon’s north and south poles. If water is discovered in these areas, it could be used as a source of energy for future human missions on the Moon. This is why many countries are actively pushing forward with lunar exploration efforts,” space expert Girish Linganna said.

JAXA is developing a rover that will move independently to look for spots on the Moon where water may be found. “It will use a drill to dig into the ground and collect soil samples. The plan is to gather data by closely analysing these samples with the observation tools installed on the rover. The rover will carry tools to measure the water content in lunar soil (called regolith), as well as equipment for drilling and collecting samples. It will also feature advanced technologies for its driving system and batteries, which are some of the first of their kind in the world. The project faces a big challenge—getting a rover that weighs several hundred kilogrammes, loaded with all these tools, to the Moon, moving it around, and analysing the samples directly on-site,” added Linganna.

As per JAXA, the rover is still in the basic design stage, and she often encounters challenges when building prototypes and conducting tests. During these tests, they spread sand similar to lunar soil at the test site and run the rover prototype over it. The team constantly adjusts the sand’s softness to match the actual Moon’s surface and tweaks the unevenness to ensure the rover can move properly. They also carefully study how much the rover’s tracks (which act like its tires) sink into the sand, making small adjustments each time. It’s a complex process with no simple solutions.

ISRO has developed advanced technology for operating lunar orbiters, landers, and rovers. However, for the LUPEX project, they will need to create a larger rover than ever before. The goal is to make a significant international impact by combining ISRO’s expertise with JAXA’s rover technology and tools for measurement and analysis.

As per Inoue Hiroka, a researcher with the Lunar Polar Exploration Project Team at JAXA’s Space Exploration Center, one of the key tasks ahead is selecting a specific landing site. The plan is to land in the Moon’s south polar region, which is believed to have a high chance of containing water. However, this area has very few flat spots that are ideal for landing and ensuring good lighting and communication. Since other countries might choose the same area, the team aims to announce their landing site as soon as they identify the best location.

If the mission gathers detailed information about water on the Moon, it could open possibilities not only for living on the Moon but also for using this water to produce fuel. This would allow us to travel to farther planets, pushing the boundaries of human exploration.