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Archetype AI’s Newton model learns physics from raw data—without any help from humans

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Archetype AI’s Newton model learns physics from raw data—without any help from humans

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Researchers at Archetype AI have developed a foundational AI model capable of learning complex physics principles directly from sensor data, without any pre-programmed knowledge. This breakthrough could significantly change how we understand and interact with the physical world.

The model, named Newton, demonstrates an unprecedented ability to generalize across diverse physical phenomena, from mechanical oscillations to thermodynamics, using only raw sensor measurements as input. This achievement, detailed in a paper released today, represents a major advance in artificial intelligence’s capacity to interpret and predict real-world physical processes.

“We’re asking if AI can discover the laws of physics on its own, the same way humans did through careful observation and measurement,” said Ivan Poupyrev, co-founder of Archetype AI, in an exclusive interview with VentureBeat. “Can we build a single AI model that generalizes across diverse physical phenomena, domains, applications, and sensing apparatuses?”

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From pendulums to power grids: AI’s uncanny predictive powers

Trained on over half a billion data points from diverse sensor measurements, Newton has shown remarkable versatility. In one striking demonstration, it accurately predicted the chaotic motion of a pendulum in real-time, despite never being trained on pendulum dynamics.

The model’s capabilities extend to complex real-world scenarios as well. Newton outperformed specialized AI systems in forecasting citywide power consumption patterns and predicting temperature fluctuations in power grid transformers.

“What’s remarkable is that Newton had not been specifically trained to understand these experiments — it was encountering them for the first time and was still able to predict outcomes even for chaotic and complex behaviors,” Poupyrev told VentureBeat.

Performance comparison of Archetype AI’s ‘Newton’ model across various complex physical processes. The graph shows that the model, even without specific training (zero-shot), often outperforms or matches models trained specifically for each task, highlighting its potential for broad applicability. (Credit: Archetype AI)

Adapting AI for industrial applications

Newton’s ability to generalize to entirely new domains could significantly change how AI is deployed in industrial and scientific applications. Rather than requiring custom models and extensive datasets for each new use case, a single pre-trained foundation model like Newton might be adapted to diverse sensing tasks with minimal additional training.

This approach represents a significant shift in how AI can be applied to physical systems. Currently, most industrial AI applications require extensive custom development and data collection for each specific use case. This process is time-consuming, expensive, and often results in models that are narrowly focused and unable to adapt to changing conditions.

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Newton’s approach, by contrast, offers the potential for more flexible and adaptable AI systems. By learning general principles of physics from a wide range of sensor data, the model can potentially be applied to new situations with minimal additional training. This could dramatically reduce the time and cost of deploying AI in industrial settings, while also improving the ability of these systems to handle unexpected situations or changing conditions.

Moreover, this approach could be particularly valuable in situations where data is scarce or difficult to collect. Many industrial processes involve rare events or unique conditions that are challenging to model with traditional AI approaches. A system like Newton, which can generalize from a broad base of physical knowledge, might be able to make accurate predictions even in these challenging scenarios.

Expanding human perception: AI as a new sense

The implications of Newton extend beyond industrial applications. By learning to interpret unfamiliar sensor data, AI systems like Newton could expand human perceptual capabilities in new ways.

“We have sensors now that can detect aspects of the world humans can’t naturally perceive,” Poupyrev told VentureBeat. “Now we can start seeing the world through sensory modalities which humans don’t have. We can enhance our perception in unprecedented ways.”

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This capability could have profound implications across a range of fields. In medicine, for example, AI models could help interpret complex diagnostic data, potentially identifying patterns or anomalies that human doctors might miss. In environmental science, these models could help analyze vast amounts of sensor data to better understand and predict climate patterns or ecological changes.

The technology also raises intriguing possibilities for human-computer interaction. As AI systems become better at interpreting diverse types of sensor data, we might see new interfaces that allow humans to “sense” aspects of the world that were previously imperceptible. This could lead to new tools for everything from scientific research to artistic expression.

Archetype AI, a Palo Alto-based startup founded by former Google researchers, has raised $13 million in venture funding to date. The company is in discussions with potential customers about real-world deployments, focusing on areas such as predictive maintenance for industrial equipment, energy demand forecasting, and traffic management systems.

The approach also shows promise for accelerating scientific research by uncovering hidden patterns in experimental data. “Can we discover new physical laws?” Poupyrev mused. “It’s an exciting possibility.”

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“Our main goal at Archetype AI is to make sense of the physical world,” Poupyrev told VentureBeat. “To figure out what the physical world means.”

As AI systems become increasingly adept at interpreting the patterns underlying physical reality, that goal may be within reach. The research opens new possibilities – from more efficient industrial processes to scientific breakthroughs and novel human-computer interfaces that expand our understanding of the physical world.

For now, Newton remains a research prototype. But if Archetype AI can successfully bring the technology to market, it could usher in a new era of AI-powered insight into the physical world around us.

The challenge now will be to move from promising research results to practical, reliable systems that can be deployed in real-world settings. This will require not only further technical development, but also careful consideration of issues like data privacy, system reliability, and the ethical implications of AI systems that can interpret and predict physical phenomena in ways that might surpass human capabilities.

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Samsung Galaxy S25 Ultra’s colors revealed in new leak

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Samsung expects to sell 22M Galaxy S25 units in first half of 2025

The Galaxy S25 series will arrive in early 2025 to try to compete for the throne as the best smartphone of the year. Samsung reserves its most advanced technologies for its “Ultra” mobile flagships, and this time will be no exception. According to reports, the company aims to make its next premium phone thinner than ever without compromising on specifications. Now, a new leak has revealed the colors in which the Samsung Galaxy S25 Ultra will be available.

The South Korean giant usually offers a wide variety of colors for its mobile devices. However, in the Galaxy S lineup, the most “gaudy” ones are reserved for the vanilla and Plus variants. On the other hand, the company resorts to more sober and business-like finishes on the Ultra models. It seems that we will see the same line in the upcoming smartphone lineup.

The Galaxy S25 Ultra could be available in these four colors

Ice Universe, a reliable tipster focused on Samsung mobile devices, revealed on X that the Galaxy S25 Ultra will be available in four colors: Black, Green, Blue, and Titanium. In any case, we cannot rule out that the smartphone will receive new colors months later. The source does not specify whether the post includes the colors that Samsung reserves exclusively for its online store.

In terms of design, the Galaxy S25 Ultra aims to stand out for its thinness in relation to the amount of tech it packs. Leaks say the device will be 8.25 mm thick. For reference, the current Galaxy S24 Ultra is 8.6 mm thick. While there are thinner flagship devices from other brands, the Galaxy S25 Ultra will still be the only one that needs to make room to store and charge the S Pen.

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The Galaxy S25 Ultra will also have a refined design for the rear camera setup. Although the sensors remain individually arranged, a thick black ring now surrounds them all. Another expected improvement in terms of design will be in reduced bezels around the display.

Some leaked key specs

Moving on to the tech specs, the device will be powered by the Snapdragon 8 Elite/Snapdragon 8 Gen 4 globally. It’s noteworthy that Samsung has not yet ruled out the Exynos 2500 chip for the vanilla and Plus models. The phone will be available in variants with 12 GB and 16 GB of RAM.

The device’s rear cameras will be 200 MP (ISOCELL HP2, main) + 50 MP ultra-wide + 10 MP (telephoto, 3x optical zoom) + 50 MP (periscope, 5x optical zoom) sensors. Lastly, the front camera on the Galaxy S25 Ultra will be a 12 MP sensor.

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Lower Decks bows out on business as usual

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Lower Decks bows out on business as usual

The following article discusses the fifth season of Star Trek: Lower Decks and older Treks.

There’s no such thing as “dead” in Star Trek, the sprawling, perpetual opus that has thrived in spite of itself for almost sixty years. What started as a cornball space-ships and punch-fights show for atomic-age kids and their parents has become (gestures around) all this. So I’m not writing too much of an obituary for Star Trek: Lower Decks despite its fifth season being its last. Given Paramount’s fluid leadership right now, I can easily imagine that decision being reversed in the future. So this isn’t so much of a goodbye as a farewell for now.

Lower Decks’ fifth season picks up not long after the fourth left off, with Tendi still repaying her debt to the Orions. I don’t think it’s a spoiler to suggest the status-quo reasserts itself soon after given, you know, all the other times this has happened. The crew of the Cerritos is then thrust into the usual sort of high-minded, lowbrow yet full of heart hijinks that we’ve come to expect. Naturally, I’m sworn to secrecy, but the fifth episode — where its title alone is a big spoiler — is a highlight.

I’ve seen the first five episodes of the season and as with any sitcom, there are a few misses in between the hits. One episode in particular is trying to reach for an old-school Frasier plotline, but it falls flat given the thinness of the characters in question. Thankfully, Lower Decks is able to carry a weak show on the back of its central cast’s charm. Sadly, as it tries to give everyone a grace note, some characters you’d expect would get more focus are instead shunted to the periphery.

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You can feel Lower Decks straining against its own premise, too. A show about people on the lowest rung of the ladder can’t get too high. As a corrective, both Mariner and Boimler use this year as an opportunity to mature and grow. I won’t spoil the most glorious running gag of the season, but their growth comes in very different ways. If there’s a downside, it’s that the show still relies too much on energy-sapping action sequences to resolve its episodes.

But that’s a minor gripe for a show that grew from the would-be class clown of the Trek world to the most joyful interpretation of its ethos. I’ve always loved how, when the chips are down, Lower Decks delights in the bits plenty of newer Treks would rather ignore. The show is, and has been, a delight to watch and something for the rest of the franchise to aspire toward.

L-R, Jerry O’Connell as Jack Ransom and Jack Quaid as Boimler in season 5 of Lower Decks streaming on Paramount+, 2024. Photo Credit: Paramount+

Paramount+

I’ve been looking for a way to describe Lower Decks’ target audience for years, but only now has it hit me. It’s a show written by, and for, the people who grew up watching Star Trek in the VHS era. Creator Mike McMahan is just four years older than me, barely a teenager when The Next Generation went off-air. So while he’d have encountered Deep Space Nine and Voyager as first-run, everything else would have been discovered through re-runs and tapes.

You can almost track that timeline of discovery as Lower Decks broadened its range of hat-tips each year it ran. Of course we got a parody of the first two Trek films in the first season — both were ever-present on Saturday afternoon TV when I was a kid — but it’s not until the third that we get a nod to First Contact. As Enterprise ran out of gas, you can feel McMahan and co’s delving into the behind-the-scenes lore and convention gossip about those later series.

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If you’ve seen , you’ll spot the gag about Harry Kim’s promotion, something the character never got on Voyager. If you’re fluent with Trek’s behind-the-scenes drama you’ll know the handful of reasons why, and why it’s funny to nod toward that now. But that’s not the only subtle gag that points a sharpened elbow into the ribs of major figures from the series creative team. I’m sure if you don’t spot them all, Reddit will have assembled a master list half an hour after each episode lands on Paramount+.

L-R , Eugene Cordero as Rutherford and Tawny Newsome as Beckett Mariner in season 5 of Lower Decks streaming on Paramount+, 2024. Photo Credit: Paramount+

Paramount+

I won’t indulge in theorizing as to why a popular and successful show like Lower Decks is ending (it’s money, it’s always money). But, as we’ve seen countless times before, it’s not as if it’s hard to revive a successful animated show when wiser heads prevail. Hell, even McMahan told he’s prepared for that, and even has some spin-off ideas in the works. But for now, let’s raise a toast to Lower Decks, the animated sitcom that became the cornerstone of modern Star Trek.

The first two episodes of Star Trek: Lower Decks season five will arrive on Paramount+, Thursday, October 24, with an additional episode landing each week for the successive eight weeks. The series and season finale will air on December 19.

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The human factor: How companies can prevent cloud disasters

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The human factor: How companies can prevent cloud disasters

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Large companies work very hard to make sure their services don’t go down, and the reason is simple — significant outages will hurt your brand and drive customers to competing products with a better track record. 

Building a reliable internet service is a hard technical problem, but for company leaders it also presents a human challenge. Motivating your engineering teams to invest in reliability work can be difficult, because it is often perceived to be less exciting than developing new features.

At scale, incentives dominate. The top tech companies employ thousands of employees and operate hundreds of internet services. Over the years, they have come up with clever ways to ensure their engineers build reliable systems. This article discusses human engineering techniques that have worked at scale across the most successful tech companies in history. You can apply these to your company, whether you’re an employee or a leader.

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Spin the wheel

The AWS operational review is a weekly meeting open to the entire company. Every meeting, a “wheel of fortune” is spun to select a random AWS service from hundreds for live review. The team under review has to answer pointed questions from experienced operational leaders about their dashboards and metrics. The meeting is attended by hundreds of employees, dozens of directors and several VPs. 

This incentivizes every team to have a baseline level of operational competence. Even if the probability of an individual team getting selected is low (at AWS, less than 1%), as a manager or tech lead on the team, you really don’t want to appear clueless in front of half the company the day your luck runs out. 

It is important that you regularly review your reliability metrics. Leaders who take an active interest in operational health set that tone for the entire organization. Spin the wheel is just one tool to accomplish this. 

But what do you do in these operational reviews? This brings us to the next point.

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Define measurable reliability goals

You would like to have a ‘high up-time’ or ‘five nines’, but what does that really mean for your customers? The latency tolerance of live interactions (chat) is much lower than that of asynchronous workloads (training a machine learning model, uploading a video). Your goals should reflect what your customers care about. 

When you review a team’s metrics, ask them to describe measurable reliability goals. Make sure you understand — and they understand — why those goals were chosen. Then, have them use dashboards to prove that those goals are being met. Having measurable goals will help you prioritize reliability work in a data-driven manner. 

It is a good idea to focus on the detection of issues. If you see an anomaly in their dashboards, ask them to explain the issue, but also ask them whether their on-call was notified of the issue. Ideally, you should realize something is wrong before your customers do. 

Embrace chaos

One of the most revolutionary mindset-shifts in cloud resiliency is the concept of injecting failure into production. Netflix formalized this concept as “chaos engineering” — and the idea is as cool as the name suggests.

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Netflix wanted to incentivize its engineers to build fault tolerant systems without resorting to micromanagement. They reasoned that if systemic failure is made to be the norm rather than the exception, engineers have no choice but to build fault-tolerant systems. It took time to get there, but at Netflix, anything from individual servers to entire availability zones are knocked out routinely in production. Every service is expected to automatically absorb such failures with no impact to service availability. 

This strategy is expensive and complex. But if you’re shipping a product where a high uptime is an absolute necessity, then failure injection in production is a very effective way to get something resembling a ‘correctness proof’. If your product needs this, introduce it as early as possible. It will never be easier or cheaper than it is today. 

If chaos engineering seems like overkill, you should at least require your teams to do ‘game days’ (simulated outage practice runs) once or twice a year, or leading up to any major feature launch. During a game day, you will have three designated roles — the first role simulates the outage, the second fixes it without knowing beforehand what was broken and the third observes and takes detailed notes. Afterward, the whole team should get together and do a post-mortem on the simulated incident (see below). The game day will reveal gaps not only in how your systems handle outages, but also in how your engineers handle them.

Have a rigorous post-mortem process

A company’s post-mortem process reveals a great deal about its culture. Each of the top tech companies require teams to write post-mortems for significant outages. The report should describe the incident, explore its root causes and identify preventative actions. The post-mortem should be rigorous and held to a high standard, but the process should never single out individuals to blame. Post-mortem writing is a corrective exercise, not a punitive one. If an engineer made a mistake, there are underlying issues that allowed that mistake to happen. Perhaps you need better testing, or better guardrails around your critical systems. Drill down to those systemic gaps and fix them. 

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Designing a robust post-mortem process could be the subject of its own article, but it’s safe to say that having one will go a long way toward preventing the next outage. 

Reward reliability work

If engineers have a perception that only new features lead to raises and promotions, reliability work will take a back seat. Most engineers should be contributing to operational excellence, regardless of seniority. Reward reliability improvements in your performance reviews. Hold your senior-most engineers accountable for the stability of the systems they oversee.

While this recommendation may seem obvious, it is surprisingly easy to miss. 

Conclusion

In this article, we explored some fundamental tools that embed reliability into your company culture. Startups and early-stage companies usually do not make reliability a priority. This is understandable — your fledgling company must be obsessively focused on proving product-market fit to ensure survival. However, once you have a returning customer base, the future of your company depends on retaining trust. Humans earn trust by being reliable. The same is true of internet services. 

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Aditya Visweswaran is a senior software engineer at Google Cloud’s security platform team.

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Ford tells some EV customers to stop using its Tesla Supercharger adapter

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Ford tells some EV customers to stop using its Tesla Supercharger adapter

Ford started offering free adapters for Tesla’s Supercharger network to owners of its EVs in February, and now it’s telling some of its customers to stop using them, reports InsideEVs. The company found a “potential issue” that could cause “reduced charging speeds over time” or even damage to the charge port itself, according to a service bulletin it’s sending to those affected.

Ford EV owners should follow the link on Ford’s notice to make sure it has the right address on file. If it is, they won’t need to do anything else to get their replacement, but if not, the company says customers need to update their address by October 24th.

Ford will supply a replacement adapter in the coming weeks and provide return instructions to send back your existing adapter – both at no cost. It is imperative that we receive all adapters affected to reduce the risk of potential vehicle damage.

Ford will reportedly start shipping replacement adapters to customers during the week of October 28th. Only “a certain recent batch” of Ford’s North American Charging Standard adapters are impacted, according to InsideEV. Both Rivian and General Motors told the outlet that they have not identified any similar issues with their own adapters.

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‘Hundreds’ of AMD’s fastest CPUs are on sale on eBay with a staggering 70% discount, but why would vendors in China dump these 128-core EPYC processors?

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AMD EPYC Genoa

In June 2023, AMD launched its EPYC “Bergamo” 9754 server-grade processor from the EPYC 9004 series, a powerhouse featuring 128 Zen 4c cores and 256 threads, with a base clock speed of 2.25 GHz and a maximum boost clock of up to 3.1 GHz.

At the time of release, the EPYC 9754 had a suggested retail price of $11,900, which is still the listed price on AMD’s website.

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The best sci-fi movies on Netflix right now

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The best sci-fi movies on Netflix right now

The sci-fi selection on Netflix is getting even thinner, as Starship Troopers, Star Trek Beyond, and Edge of Tomorrow are all leaving by the end of October. Some of the replacements are Elysium and A Quiet Place Part II, both of which are very good movies. Having said that, Netflix really needs to beef up its available titles for science-fiction lovers, because we shouldn’t have to go on a scavenger hunt through the algorithm just to find worthy additions.

Keep reading for the rest of the best sci-fi movies on Netflix. We’ll always update the list every month to reflect the latest additions and subtractions from Netflix’s lineup. Hopefully, we’ll have a wider selection in November.

We’ve curated guides to the best sci-fi movies on Amazon Prime Video and the best sci-fi movies on Hulu, too. Need more recommendations? Then check out the best new movies to stream this week, the best movies on Netflix, the best movies on Hulu, the best movies on Amazon Prime Video, the best movies on Max, and the best movies on Disney+.






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