Category Archives: Ai
Intel Capital backs AI construction startup that could boost Intels own manufacturing prospects – TechCrunch
Intel could be giving its burgeoning foundry ambitions a much-needed shot in the arm, as the chip giants venture capital arm today revealed that its making a strategic investment in an Israel- and U.K.-based AI construction startup.
Intel Capital is leading a $15 million investment into Buildots, a company that uses AI and computer vision to create a digital twin of construction sites. The six-year-old company works with construction giants such as Pomerleau, NCC and Ledcor, serving them with 360-degree cameras to regularly capture on-site data to track project progress, identify bottlenecks and optimize workflows.
Buildots had previously raised around $106 million, with its most recent $60 million tranche coming two years ago.
While Intel Capital has plowed billions into AI startups through the years, its decision to buy a stake in Buildots is particularly notable right now, coming as its parent company doubles down on efforts to increase its own manufacturing capacity while trying to keep costs in check.
A few years back, Intel revealed plans to invest$20 billion in two new fabrication facilities (or fabs) at its Ocotillo campus in Arizona. At the same time, Intel also launched a new foundry business recently rebranded as Intel Foundry with a view toward manufacturing chips designed by other companies.
These two new Arizona factories, dubbed Fab 52 and Fab 62, are expected to hit completion by early 2025. But they are among a number of massive construction projects Intel has on the go around the world right now, including plans for two new plants in Ohio that could cost up to $28 billion. These were originally expected to start bearing fruit in 2025, though the company recently announced it would have to delay these plans by a year, citing market challenges.
So Intel is something of a construction powerhouse, with its current spend across four U.S. states alone pegged at around $100 billion spanning new builds and refurbs. Pressure is mounting, though, as its recent earnings showed that its Foundry business losses widened last year, while the company faced another setback when regulatory hurdles forced it to pull the plug on a $5.4 billion merger with contract chipmaker Tower Semiconductor. (The pair instead struck a commercial partnership that will see Intel provide foundry services to Tower as part of a $300 million investment.)
To help with these various manufacturing endeavors, Intel is also set to receive $8.5 billion in government funding as part of U.S. plans to bring more chip manufacturing in-house, as it were.
However, one of the best ways to cut costs is to improve efficiencies, which is where Buildots could help. Just recently, the company launched a new AI-powered delay forecast feature that claims to predict when delays might occur to help project managers take preemptive action.
Buildots said at the time of the launch that during beta testing on major construction sites, the delay forecast feature was able to reduce delay times by up to 50% in some scenarios.
Historically, the construction industry was always deemed to have been slower than most to embrace digitization. This is in part due to the complexity and unique nature of each project, as well as the multi-stakeholder coordination required, spanning architects, contractors, engineers, suppliers, regulators and more. But there are signs that this is changing, particularly with the advent of AI, which while unable to build a tower block is showing some promise in terms of helping to reduce timelines on the operational side.
Neither Intel nor Buildots would directly confirm whether they are already working together, though Buildots has alluded to this on social media in the past with references to collaborations with industry giants like Intel.
In a statement issued to TechCrunch, Intel Capitals investment director Lisa Cohen said that Intels own experiences in the construction realm have helped it understand the need to drive efficiencies through technology.
Intels first-hand experience building some of the largest and most complex construction projects in the world has certainly played a role in leading us to appreciate the tremendous potential AI technology in general, and Buildots specifically, holds in terms of revolutionizing construction process management and driving efficiency to new levels, Cohen said.
As a result of the investment, Cohen will now be joining Buildots board of directors. Other investors in the round include Israels OG Tech Partners among other unnamed previous investors.
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Samsung is bringing AI to Bixby this year – TechRadar
Were now entering the age of the AI smartphone, with Google and Apple, in particular, having rolled out or announced a wealth of AI features in recent months. Samsung offers quite a few AI tools too, but so far its own digital assistant Bixby hasnt received an AI upgrade.
That looks set to change soon, though, as CNBC reports that this year Samsung will launch an upgraded version of Bixby based on its own AI models. The site heard this tip directly from TM Roh (the head of Samsungs mobile division), so you can take it as confirmed.
Sadly, Roh didnt get more specific about exactly when this AI upgrade to Bixby will roll out, but with less than half the year left, we shouldnt be waiting too long.
Roh also didnt say exactly what improvements this Bixby-focused AI overhaul will bring, but based on what were seeing in other AI-powered assistants, we have a good idea of what to expect.
For one thing, this update will probably make Bixby more conversational, so it can keep track of extended interactions with multiple questions and follow-ups. This upgrade may also allow Bixby to carry out more complex tasks, such as those which require it to interact with multiple apps.
So, this upgrade should be appreciated by fans of Bixby, though Samsung also told CNBC that it will continue allowing alternative options on its phones, such as Google Assistant, so if youre not a Bixby fan youll still have options.
Mind you, even in its current form, it might be worth giving Bixby a second chance. In a recent test, we found that Bixby outperformed both Siri and Gemini, and thats before this AI overhaul, which with any luck will make it even better.
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He created Oculus headsets as a teenager. Now he makes AI weapons for Ukraine – NPR
Palmer Luckey, 31, founder of Anduril Industries, stands in front of the Dive-LD, an autonomous underwater drone at company headquarters in Costa Mesa, Calif. Anduril recently won a U.S. Navy contract to build 200 of them annually. Philip Cheung for NPR hide caption
COSTA MESA, Calif. Its easy to spot Palmer Luckey. Hes the guy with the mullet and the goatee, almost always dressed in khaki shorts, flip flops and bright Hawaiian shirts.
As he gives a tour of Anduril, the artificial intelligence weapons company he founded just south of Los Angeles, hes in his standard business attire.
"This is one of my Dungeons and Dragons Hawaiian shirts," he explains. "You've got an elder dragon. You've got a fighter, a couple of wizards. I wear a lot of Hawaiian shirts because I like them, and I can get away with it.
He can get away with it because he's been a billionaire since his early 20s.
When still a teenager, Luckey launched his first tech company, Oculus, the virtual reality headset for gaming. He sold it a couple years later to Facebook for $2 billion.
Now 31, Luckey took that fortune and founded a new company, Anduril, thats making AI intelligence weapons like drones and submarines.
The Pentagon is buying them, keeping some for itself and sending others to Ukraine. Seven years after it started, Anduril says it's selling its autonomous weapons to about 10 countries worldwide.
In a showroom with its weapons on display, Luckey describes the company's ALTIUS drone.
"It's a drone that fires out of a tube into the air and then unfolds itself, extends its wings, extends its tail, unfolds the propeller and transforms itself into a small airplane," he says. "It can carry up to a 30-pound warhead. So you've got a lot of punch in this thing.
Palmer Luckey walks in the showroom featuring Anduril's artificial intelligence weapons. The company says it can build AI weapons much faster and cheaper than traditional military contractors who make large weapon systems, like fighter jets and tanks. Philip Cheung for NPR hide caption
Anduril is among a growing number of tech companies making artificial intelligence weapons and boldly proclaiming theyll change the way the U.S. and its allies wage war.
In short, the aim is more tech doing the fighting and fewer troops in harm's way. The revolution hasn't happened yet. But these companies are shaking up an industry long dominated by massive firms such as Lockheed Martin and General Dynamics, which build large, traditional weapons, from fighter jets to tanks, designed to last decades.
Anduril, named after a sword in Lord of the Rings, has a very different approach.
"I had this belief that the major defense companies didn't have the right talent or the right incentive structure to invest in things like artificial intelligence, autonomy, robotics," says Luckey. "And the companies that did have expertise, like Google, like Facebook, like Apple, were refusing to work with the U.S. national security community."
Andurils pitch is AI weapons, built in less time and at a lower cost than traditional defense contractors.
The man spreading this message is an iconoclastic figure in the largely liberal tech community for his work with the military, and his outspoken politics, including long-standing support for Donald Trump.
But Palmer Luckey is hard to ignore.
Just days after Russias full-scale invasion of Ukraine in 2022, Luckey made his way to the capital Kyiv, and met Ukrainian President Volodymyr Zelenskyy.
"Anduril has had hardware in Ukraine since the second week of the war. So we immediately got involved," Luckey says.
A Ukrainian soldier operates a drone in the Zaporizhzhia region of southeastern Ukraine on June 14. Ukraine has been using cheap, civilian drones that it buys off the Internet. But Russia has responded with electronic jamming, often rendering such drones useless. Ukraine is now making its own drones and is looking for autonomous systems that are difficult to detect and stop. Andriy Andriyenko/AP hide caption
The Ukraine war has become a laboratory for an array of high-tech systems.
Most striking is Elon Musk's Starlink satellite network that provides critical communications for Ukraines military.
However, in this emerging industry of AI weapons, critics say a lot of bugs still need to be worked out.
In several off-the-record conversations, people working closely with Ukraines military say many new weapons, from a range of companies, still have flaws, are vulnerable to Russian counter-measures, and simply have not yet performed as advertised.
So far, they add, these weapons have had a limited impact and have not changed the wars trajectory.
Andurils CEO Brian Schimpf acknowledges the difficulties, but sees them as surmountable.
Brian Schimpf, the CEO of Anduril, stands next to a a launch system for the Altius drone at company headquarters. Schimpf acknowledges that operating in Ukraine is a challenge, but says Anduril's AI weapons are designed to be updated quickly to adapt to changing conditions. Philip Cheung for NPR hide caption
"Ukraine is a very challenging environment to learn in," he says. "Ive heard various estimates from the Ukrainians themselves that any given drone typically has a life span of about four weeks. The question is can you respond and adapt?
Jacquelyn Schneider, who studies military technology as a fellow at the Hoover Institution, says the war has dramatically increased the pace of innovation.
"Technologies that worked really well even a few months ago are now constantly having to change," she says. "And the big difference I do see is that software changes the rate of change."
Weapons systems in Ukraine need to be updated frequently, just like the software on a phone or computer.
"If you're buying a weapons platform that cannot be very easily modified for these software innovations, then the weapon system will become useless or not as effective in a very short period of time," she adds.
P.W. Singer, an author who writes about war and tech, says, "There's this mythology of innovation as if it happens in one place."
The reality is "there's a lot of cool, exciting stuff happening in the big defense primes. There's a lot of cool, exciting stuff happening in the big-tech Silicon Valley companies. There's a lot of cool, exciting stuff happening in small startups," he says.
He also says AI weapons like drones should be seen as an addition not a replacement for existing weapons.
"No one is saying, 'Well, that means there's no need for our traditional military. There's no need for manned airplanes.' Of course, you need both," he says.
Anduril's Altius 600 drone hangs in the showroom at company headquarters in southern California. Most drones are remotely controlled by a pilot. The Anduril drones can be programmed before takeoff to search, find and strike a target without being guided by a remote pilot. Philip Cheung for NPR hide caption
In the face of Russia's big offensive two years ago, Ukrainians turned to small, cheap civilian drones made in China and available on the Internet. The Ukrainians attached grenades and other small explosives, then dropped the weapons down the open turrets of unsuspecting Russian tanks.
In many instances, a $1,000 drone was taking out a multi-million-dollar tank or other expensive Russian weaponry, as well as inflicting casualties on Russian troops. But it's getting much harder for the Ukrainians to carry out these kinds of attacks.
The Russians have responded with electronic jamming, blocking the signal the drone was sending to the Ukrainian soldier operating it. This renders the drone useless.
This is where Anduril is trying to step in. The company's AI drones can be programmed before takeoff to search on their own for Russian tanks or other targets.
Once launched, these drones dont need guidance from a Ukrainian soldier making them very hard to detect and stop, says Luckey.
"The autonomy onboard is really what sets it apart," he says. "It's not a remote controlled plane. There's a brain on it that is able to look for targets, identify targets and fly into those targets."
Of course, this raises questions about whos responsible if something goes wrong like hitting civilians.
In a recent report submitted to the United Nations, Human Rights Watch called for "the urgent negotiation and adoption of a legally binding instrument to prohibit and regulate autonomous weapons systems."
The organization says more than 270 groups and 70 countries have now joined its Campaign to Stop Killer Robots.
However, Andurils Brian Schimpf says AI weapons are "not about taking humans out of the loop. I don't think that's the right ethical framework. This is really about how do we make human decision-makers more effective and more accountable to their decisions."
Ukraine now makes its own sea drones essentially jet skis packed with explosives which have inflicted serious damage on the Russian navy in the Black Sea.
Luckey puts on a virtual reality headset to show an augmented reality model of Andurils Dive-LD underwater drone at Anduril headquarters. Philip Cheung for NPR hide caption
Luckey shows me Andurils version, an underwater drone called Dive-LD, in an old, largely vacant industrial building thats part of Andurils otherwise shiny campus.
We put on virtual reality headsets an updated model of the one Luckey created for an augmented look at the sub.
"It's an autonomous underwater vehicle that is able to go very, very long distances, dive to a depth of about 6,000 meters, which is deep enough to go to the bottom of almost any ocean," he says.
Last month, Anduril won a U.S. Navy contract to build more than 200 of them annually.
Luckey has pursued his interests in tech, business and politics since his teen years. Way back in 2011, Luckey wrote to Donald Trump and urged him to run for president.
"I said, 'Hey, consider me one of the people who thinks it's good to have a businessperson in office, somebody who's familiar with signing both sides of a check.'"
He still supports Trump today.
"In general, yeah, I think he'd make a good commander in chief," he adds.
Yet from a business perspective, he says hes not that concerned about who wins in November.
"We made a lot of money under Trump. We made even more money under Biden. I think we're going to continue expanding whoever is in office next," said Luckey.
More AI weapons are coming, he says, no matter whos in the White House.
Greg Myre is an NPR national security correspondent. Follow him @gregmyre1.
NPR producer Kira Wakeam contributed to this report.
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He created Oculus headsets as a teenager. Now he makes AI weapons for Ukraine - NPR
AMD acquires Silo AI in $665 million deal to boost its AI solutions pedigree deal should be wrapped up later this year – Tom’s Hardware
AMD hassigned a definitive agreement to acquire Silo AIfor $665 million in cash. Silo AI specializes in the integration of AI capabilities into solutions used by businesses, and its takeover will help AMD to significantly boost its AI capabilities and deliver end-to-end AI solutions comprising AI models, software, and hardware, for big customers. The deal is anticipated to be finalized in the latter half of 2024.
Silo AI is renowned for its team of AI scientists and engineers who specialize in creating customized AI models and solutions, and their expertise spans various sectors, including cloud computing and embedded systems. The company has been instrumental in helping customers like Allianz, Philips, Rolls-Royce, and Unilever to quickly integrate AI solutions designed to meet the unique needs of each enterprise into their products and services that cover a wide array of markets. The company is also known for developing open-source multilingual large language models (LLMs) like Poro and Viking.
Also, Silo AI has collaborated with institutions to optimize AI model training on LUMI, Europe's fastest supercomputer, which is powered by over 12,000 AMD Instinct MI250X GPUs. This collaboration has resulted in the development of advanced open-source models for European languages.
The acquisition of Silo AI is a strategic move for AMD as it immediately enhances its AI capabilities and accelerates its AI strategy as with an experienced team it will be easier for the company to land customers in the enterprise space. Essentially, it will now be able to offer not only hardware, but also software for enterprise customers, which is a good way to compete against Nvidia.
"At Silo AI, our mission from the start has been to build an AI flagship company. Today's announcement is a logical next step in that pursuit as we join forces with AMD to shape the future of AI computing," said Peter Sarlin, CEO and co-founder of Silo AI. "We have a well-established history of building successful AI products and delivering value to our customers. We look forward to becoming part of AMD to further scale our impact and develop enterprise solutions and AI models that address the most complex challenges with deploying AI at scale today."
Silo AI's CEO and co-founder, Peter Sarlin, will remain at the helm of the Silo AI team within the AMD Artificial Intelligence Group led by AMD's senior vice president, Vamsi Boppana.
Over the past year, AMD has invested over $125 million in a dozen AI companies and acquired Mipsology and Nod.ai to expand its AI ecosystem and support its partners.
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"Silo AI's team of trusted AI experts and proven experience developing leadership AI models and solutions, including state-of-the-art LLMs built on AMD platforms, will further accelerate our AI strategy and advance the build-out and rapid implementation of AI solutions for our global customers," said Vamsi Boppana, senior vice president of the Artificial Intelligence Group at AMD.
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$10000 AI-generated, 3D-printed liquid nitrogen container tested supercools CPUs up to 3 times faster than … – Tom’s Hardware
Skatterbencher and three industry-leading partners have completed a feasibility study to see if its possible to build a liquid nitrogen (LN2) container using generative AI and additive manufacturing techniques, also known as 3D printing. In a blog post and YouTube video, the partners show that its possible, but perhaps not financially wise, for the benefits obtained.
Pieter of Skatterbencher is an expert in overclocking and teamed up with three industry-leading companies to explore the possibilities of AI and 3D printing for LN2 cooling. These included Diabatix, a Belgian company pioneering the use of generative AI in thermal solutions, and 3D Systems, an expert in additive manufacturing. Rounding out the partnership was ElmorLabs, a well-known name in overclocking.
The project used the ElmorLabs Volcano CPU LN2 container as a reference design. It tasked Diabatixs ColdStream Next AI platform with designing a new LN2 container to improve the reference design. Once the design was complete, the team sent it to 3D Systems to produce a prototype using oxygen-free copper powder.
The prototype's design and manufacture cost $10,000. In comparison, the ElmorLabs Volcano CPU LN2 container used as a reference design sells for just $260.
The base performance tests compared the AI-designed LN2 container with the ElmorLabs Volcano in three categories:
In testing, the AI-generated LN2 container blew away the Volcano in the cool-down test. It reached -194 Celsius in just under 56 seconds. The Volcano took almost three minutes three times as long as the prototype. The heat-up test also went in the AI designs favor, but not as dramatically. The container heated to 20 Celsius 1.2 times faster than the Volcano, more than 30 seconds faster.
Finally, the AI-designed LN2 container proved 20% more efficient than the ElmorLabs design. Using 500mL of liquid nitrogen, the Volcano cooled down to just -100 Celsius, while the AI-designed prototype went down to -133 Celsius.
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Those tests dont reflect practical considerations, so the team also conducted further tests of a more practical nature:
The team found that while the AI-designed container did beat the ElmorLabs Volcano in real-world tests, the improvements were not nearly as pronounced. Given the dramatic price difference between the AI design and the existing product, the AI design is not a cost-effective alternative.
With the initial testing out of the way, SkatterBencher and its partners may look into performance and cost optimizations and perhaps change the intended use to be for even higher-power CPUs, like the AMD Ryzen Threadripper. The team would also like to commercialize the design but likely has a fair bit of work ahead of it to make it commercially viable.
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Meta Will Enable Influencers To Create AI Versions of Themselves – Social Media Today
Its been in development for a while, and today, Metas launching the first stage of its AI Studio platform, which will enable creators on Instagram to build AI versions of themselves that can interact with fans via DM.
As you can see in this example, Meta's custom AI bots, currently in beta, and in limited testing with selected creators, will be able to answer questions in the style of that account.
The AI bot will have a stars icon on the message tab, signalling that this is a bot response stream, while there are also disclaimer notes in the chat, explaining that it's an AI bot that you're engaging with.
So it *should* be clear to all that you're not talking to the actual person or account holder. But then again...
Meta CEO Mark Zuckerberg made the announcement during an interview with YouTuber Kane Sutter, in which he also discussed various elements of Metas broader AI plans.
Most of Zucks comments are fairly vague and broad-reaching, with a few indicators of its coming AI updates (improved translation, hologram-like projections of real people in VR).
But the main announcement is the launch of live testing of AI Studio with selected IG creators in the U.S.
Zuckerberg says that AI Studio will enable creators to build an AI agent version of themselves to interact with their community. The process, built into Instagram (which app researcher Alessandro Paluzzi uncovered recently), will provide various prompts and tools to generate these AI bot variations.
The main focus, or the simple use case, according to Zuckerberg, is to answer fact-based queries, with the more challenging element coming in answers that are more creative, and replicate the style of the creator. Zuckerberg says that creators will have the freedom to train their bots on different aspects of their social media presence, and through this, that should enable them to generate more life-like replicas of themselves.
Yet, as noted, Meta also doesnt want to trick people into thinking theyre engaging with the real person. Zuckerberg noted that they're still working on the AI disclosure elements, but there are various signifiers in-stream.
But the bigger question that I have is Why? Why would people want to engage with a bot that sounds like a person of profile, when they're not actually engaging with a human at all?
I mean, I get the basic use case, in regards to creators getting a heap of queries, and only having so much time to personally respond. This is the fact-based element, where the bots will be able to provide, essentially, generic answers to common questions, in the style of the creator. But expanding into other areas seems inherently deceptive, and also, counter to the entire focus of social media platforms.
Right?
Sutter posed the same question in his interview with Zuckerberg, noting that there will be some trepidation, from creators and their audiences, about eroding that real connection within the medium. Zuckerberg played it down somewhat in his response, but really, there doesnt seem to be any real value in having AI bots that simulate actual humans, especially within apps that are geared around authentic connection.
It seems like a step away from the core use case of social, and into something else, a platform where bots end up engaging with bots, and real humans are sidelined in favor of automated engagement.
Havent users been complaining about bots for years? Hasnt inauthentic interaction always been a problem on social apps? But now we're not only encouraging it, but directly using it to replace humans.
Because the technology is better now, and more convincing? Is that the reason why people have always been annoyed by bots?
I dont know, it doesnt feel like the right way to lean into the AI trend, but Meta seems convinced that robot versions of celebrities and influencers will be a valuable add on, for some reason.
Zuckerberg also notes that, eventually, people will also be able to create UGC AI characters as well, that can interact with people in different ways and styles.
Though again, is there any actual demand for this? Will it add value?
Im not sure that Metas initial experiments with celebrity-influenced bots really caught on, but Metas pushing ahead, which will bring more endorsed bot engagement in-stream.
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Meta Will Enable Influencers To Create AI Versions of Themselves - Social Media Today
Zuckerberg disses closed-source AI competitors as trying to ‘create God’ – TechCrunch
Riffing on what he sees for the future of AI, Meta CEO Mark Zuckerberg said in an interview published Thursday that he deeply believes that there will not be just one AI. Touting the value of open source to put AI tools into many peoples hands, Zuckerberg took a moment to disparage the efforts of unnamed competitors who he sees as less than open, adding that they seem to think theyre creating God.
I dont think that AI technology is a thing that should be kind of hoarded and that one company gets to use it to build whatever central, single product that theyre building, Zuckerberg said in a new YouTube interview with Kane Sutter (@Kallaway).
I find it a pretty big turnoff when people in the tech industry talk about building this one true AI, he continued. Its almost as if they kind of think theyre creating God or something and its just thats not what were doing, he said. I dont think thats how this plays out.
I get why, if youre in some AI lab you want to feel like what youre doing is super important, right? Its like, Were building the one true thing for the future. But I just think, like, realistically, thats not how stuff works, right? Zuckerberg explained. Its not like there was one app on peoples phones that people use. Theres not one creator that people want all their content from. Theres not one business that people want to buy everything from.
In the conversation, Zuckerberg said there needs to be a lot of different AIs that get created to reflect peoples different interests. The company also on Thursday announced early tests of its AI Studio software in the U.S. that will allow creators and others to build AI avatars that will be able to reach people through Instagrams messaging system. The AIs will be able to answer questions from their followers and chat with people in a fun way but will be labeled as AI to not cause confusion.
When referring to companies that build closed AI platforms, the Meta CEO said he didnt believe this is how to create the best experiences for people.
You want to unlock and unleash as many people as possible trying out different things, he continued. I mean, thats what culture is, right? Its not like one group of people getting to dictate everything for people.
His comments feel a bit like sour grapes, as they arrive shortly after reports emerged that Meta had tried to negotiate with Apple to integrate its AIs into Apples operating systems, instead of only working with OpenAI at launch, but got shot down. According to Bloomberg, Apple decided to not move forward with formal discussions with Meta because it didnt believe its privacy practices were strong enough.
Without a deal, Meta loses access to potentially billions of iPhone users worldwide. But it appears that Metas plan B is to build technology that expands beyond the smartphone.
In the interview, Zuckerberg touched on the progress the company is seeing with the Ray-Ban Meta smart glasses, for example, saying that its path would one day converge with the work being done now on full holographic displays. However, the former will have more appeal in the near term, he said.
I actually think you can create a great experience with cameras, and a microphone, and speakers and the ability to do multimodal AI, even before you have any kind of display on these glasses, he noted. Plus, not having a display keeps the costs down. Metas smart glasses are around $300, and the Meta Quest Pro is $1,000, for comparison.
Zuckerberg said there will be three different products ahead of convergence: display-less smart glasses, a heads-up type of display and full holographic displays. Eventually, he said that instead of neural interfaces connected to their brain, people might one day wear a wristband that picks up signals from the brain communicating with their hand. This would allow them to communicate with the neural interface by barely moving their hand. Over time, it could allow people to type, too.
Zuckerberg cautioned that these types of inputs and AI experiences may not immediately replace smartphones, though. I dont think, in the history of technology, the new platform it usually doesnt completely make it that people stop using the old thing. Its just that you use it less, he said.
For instance, people now use smartphones to do things they may have done on their computers 10 to 15 years ago.
I think thats gonna happen with glasses, too, he said. Its not like were going to stop having a phone. Its just that its going to stay in your pocket, and youll take it out when you really need to do stuff with it. But more and more, I think people will just start saying, Hey, I can take this photo with my glasses. I can ask this question to AI, or I can send someone a message its just a lot easier with glasses, Zuckerberg said.
I wouldnt be surprised if 10 years from now, well probably still have phones, but its probably going to be much more intentional in usage as opposed to just reflexively reaching for it and grabbing it for any technological thing that you want to do, he said.
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Zuckerberg disses closed-source AI competitors as trying to 'create God' - TechCrunch
Microsoft’s Guide to using AI to become more Productive – Medium
Hey there, Im Devansh. I write for an audience of ~200K readers weekly. My goal is to help readers understand the most important ideas in AI and Tech from all important angles- social, economic, and technical. You can find my primary publication AI Made Simple over here, message me on LinkedIn, or reach out to me through any of my social media over here. I work as a consultant for clients looking to integrate AI in their lives- so please feel free to reach out if you think we can work together.
Teams everywhere are concerned about how to integrate AI into their workflows most effectively. If your organization has lots of money to burn, you could pay McKinsey consultants 400 USD/hour to create pretty slides based on recommendations from ChatGPT and spend 5 hours weekly in meetings to explore synergies and best practices. But for those of you without that luxury, one of the best resources is to look at the research done by the productivity teams at major companies. These companies have dedicated teams that interview their employees, study workflows, and extract insights from various internal and external experiments conducted on productivity.
Today, we will be looking at Microsofts excellent Microsoft New Future of Work Report 2023 to answer a key question- how can we leverage AI to make our work more productive? We will be studying the report brings to pull out interesting insights on-
1. How LLMs impact Information Work:
Task completion times for lab studies of Copilot for M365 (Cambon et al. 2023)
In a lab experiment, participants who scored poorly on their first writing task improved more when given access to ChatGPT than those with high scores on the initial task. Peng et al. (2023) also found suggestive evidence that GitHub Copilot was more helpful to developers with less experience. In an experiment with BCG employees completing a consulting task, the bottom- half of subjects in terms of skills benefited the most, showing a 43% improvement in performance, compared to the top half whose performance increased by 17%(DellAcqua et al. 2023).
I would take these results with a grain of salt, however. High-skill performers often do different things to their low-skilled counterparts, something that standardized tests are unable to measure. League 2 player Erling Haaland is a better footballer than me not just because he can beat me on performance-related tests, but also because he does 30 things that I dont. These 30 things are often much more difficult to measure. As we figure out how to use AI more effectively (and how to measure the results better), AI might actually increase the performance disparity between skilled and unskilled workers (most technology tends to reinforce differences, not reduce them). We already see some signs of this.
2. LLMs and Critical Thinking:
3. On Human-AI Collaboration:
4. LLMs for Team Collaboration and Communication:
5. Knowledge Management and Organizational Changes:
6. Implications for Future Work and Society:
Well spend the rest of this article discussing these ideas in more detail. Lets get right into it.
The following image summarizes the key themes very well-
Generative AI makes a clear, undeniable contribution to reducing the cognitive load from repetitive work, significantly improving experience- 68% of respondents agreed that Copilot actually improved quality of their workparticipants with access to Copilot found the task to be 58% less draining than participants without accessAmong enterprise Copilot users, 72% agreed that Copilot helped them spend less mental effort on mundane or repetitive tasks.
The impacts on quality are a bit more diverse. In a meeting summarization study, we see a slight reduction in performance, in the meeting summarization study where Copilot users took much less time, their summaries included 11.1 out of 15 specific pieces of information in the assessment rubric versus the 12.4 of 15 for users who did not have access to Copilot. This is not a super-significant difference but it definitely highlights the importance of having a human in the loop to audit the generation. In this sense, it seems like LLMs can be very helpful in creating a good first draft very quickly- leaving the refinement and improvements to the user (something 85% of the respondents agreed to).
On more domain-specific tasks, LLMs can introduce a very noob-friendly meta by raising the performance floor- In the other direction, the study of M365 Defender Security Copilot found security novices with Copilot were 44% more accurate in answering questions about the security incidents they examined. You can see something similar for yourself- with tools like DALLE that allow anyone to make good images. This is what leads to the impression that AI can help replace experts in their respective fields. For example, the usage of Github Copilot leads to a significantly better performance for programmers-
However, the reality is a lot more complicated. While such tools can be very helpful- they also introduce all kinds of unpredictable errors and vulnerabilities in systems. This is where Domain Expertise is key, since it will help you evaluate and modify the base output to your needs (the first draft concept shows up again). The most effective usage of LLMs often involves guiding it towards the correct answer. So for knowledge workers- it is crucial to know what to do. LLMs/Copilots can take care of the how.
Using AI for knowledge work always comes with the risk of overreliance and lax evaluations (we humans are prey to something called the automation bias, where we give undue weightage to any decision taken by an automated system). This is why a large part of my work involves building rigorous evaluation pipelines, better transparency systems, and controlling for random variance for my clients. Without these teams can end up with an incomplete picture of their system- leading to catastrophically wrong decisions (cue AirCanada not testing their system and it offering refunds to people).
With all of that covered, lets move on to the next section. How can we use AI to improve critical thinking and creativity? How can humans use AI effectively?
To answer this question, lets first understand the biggest problems faced by a lot of teams- cognitive overload, knowledge fragmentation, and a lack of feedback.
When it comes to reducing cognitive overload, AI-based tools can be used for delegations, planning, and quick load balancing. Once again, the goal here isnt to have AI do this perfectly, but for it to save time for users that would otherwise do this manually-
Next, lets cover knowledge fragmentation. Large organizations have a lot of projects happening, and key people often leave due to turnover, promotions, or retirement. In this environment, keeping track of all that is happening and already done becomes impossible- and there is a lot of wasted effort reinventing the wheel.
Knowledge fragmentation is a key issue for organizations. Organizational knowledge is distributed across files, notes, emails (Whittaker & Sidner 1992), chat messages, and more. Actions taken to generate, verify, and deliver knowledge often take place outside of knowledge deliverables, such as reports, occurring instead in team spaces and inboxes (Lindley & Wilkins 2023). LLMs can draw on knowledge generated through, and stored within, different tools and formats, as and when the user needs it. Such interactions may tackle key challenges associated with fragmentation, by enabling users to focus on their activity rather than having to navigate tools and file stores, a behavior that can easily introduce distractions (see e.g., Bardram et al. 2019). However, extracting knowledge from communications raises implications for how organization members are made aware of what is being accessed, how it is being surfaced, and to whom. Additionally, people will need support in understanding how insights that are not explicitly shared with others could be inferred by ML systems (Lindley & Wilkins 2023). For instance, inferences about social networks or the workflow associated with a process could be made. People will need to learn how to interpret and evaluate such inferences
This is a theme we see in a few different studies. Google has an excellent publication into what software devs want from AI. Both the 2nd and 3rd reason mentioned below can be addressed (atleast partially) by using AI to aggregate insights across platforms and unify them into one place that people can refer to.
We covered that publication in-depth over here. The final section- which talks about concrete steps that orgs must take to fully unlock their AI potential will be relevant to you, even if youre not an AI/Tech Company. For now, the simple takeaway is to encourage active documentation/logging so that your AI has plenty of data, and to invest heavily into AI systems that can interact with that Data in a useful manner.
We can summarize the main ideas in this section as follows-
Combine this with the usage of Copilot-like tools for knowledge workers, and you get something really powerful. Lets end this with a discussion the implications and the future of work.
As with any disruptive technology, AI will change not only how we do things, but also fundamentally what we do and what becomes important. Were already seeing some of this. Slide 11 brings up an interesting possibility- where knowledge work may shift towards more analysis and critical integration as opposed to raw generation.
As opposed to a naked replacement that many people claim- I think that people will simply have to dedicate a lot more time to the evaluation. Checking outputs, sources, and the base analysis of the AI are all a must, and well all probably spend a lot more time on that. Thus, there is a lot to be gained by investing in your skills for the same (or building tools there).
Similarly, soft skills and the general ability to push other people to get shit done would become even more important-
Skills not directly related to content production, such as leading, dealing with critical social situations, navigating interpersonal trust issues, and demonstrating emotional intelligence, may all be more valued in the workplace
-(LinkedIn 2023)
With a powerful tool like AI, accessibility also becomes an important discussion point. There are two important dimensions of accessibility-
The second is critical, but much harder. Open-sourcing research/other important ideas in AI is my goal and the reason why my primary publication- AI Made Simple- doesnt have any paywalls. However, thats a very small part of what needs to be done. I have some ideas on what we can do to push things forward- but this is something that needs a lot open conversations from a lot of people. If you have any ideas/want to discuss things with me, shoot me a message and lets talk. Once again, you can find my primary publication AI Made Simple over here, message me on LinkedIn, or reach out to me through any of my social media over here.
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Microsoft's Guide to using AI to become more Productive - Medium
Who of us will survive the AI takeover? – Osceola Sun
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It’s not just Nvidia: AI interest sends these stocks higher – The Washington Post
Attention around artificial intelligence has driven chipmaker Nvidia sharply higher in recent years, to the point where it briefly was the worlds most valuable company but AI investors are targeting other stocks, too.
Some hardware-focused companies in the AI supply chain have seen blistering stock price gains in the past 18 months, and the process of implementing AI across large organizations is already driving business for leading software firms.
The hype has drawn comparisons to the dot-com bubble of the late 1990s, when many internet start-ups saw massive, short-lived investment gains before crashing down. But this time, some analysts say, much of the AI interest has been concentrated on a much smaller number of established technology firms, and it is linked to significant corporate spending happening now.
The impact of generative AI is not as broad-based as initially imagined, said Chirag Dekate, a vice president and analyst at Gartner. There are a very specific entities that are providing the foundational technology.
Here are some publicly traded companies riding a wave of artificial intelligence investment.
Co-founded by technology investor Peter Thiel, this company has evolved from an organization doing mostly defense and intelligence work into a data company serving enterprises of all sorts. Under chief executive Alex Karp, the company has built a growing suite of artificial-intelligence offerings.
It is among a growing industry that implements AI technology for large organizations, a sector that also includes C3AI and the consulting firms Deloitte, Accenture and Ernst & Young, according to Dekate.
Palantirs platform examines a companys data and provides examples of how AI can be employed within an organization. Wedbush Securities analyst Dan Ives said he sees Palantir as the golden child of AI because of its emphasis on the practical use of artificial intelligence within large organizations.
Nvidia chips are just the start, but it all comes down to use cases, Ives said.
The contract manufacturing giant has a ubiquitous presence in the global tech industry with its production of computer chips built into consumer products like smartphones and cars, as well as military satellites and weapons systems.
Deepwater Assets Munster says his firm is invested in TSMC, along with Broadcom and Vertiv, as part of a broader play to capitalize on the growth of AI-enabling hardware. A company called Onto Innovation, which handles specialized measurement for chip construction, is also seen as a niche beneficiary.
Hardware is the play right now because were seeing tangible improvements to their business. They are trading at software-like multiples, Munster said. The hardware for this is just getting built.
Original post:
It's not just Nvidia: AI interest sends these stocks higher - The Washington Post