LinkedIn, the Microsoft-owned social platform, has made a name for itself primarily as a platform for people looking to network and pick up knowledge for professional purposes, and for recruitment — a business that now has more 1 billion users. Now, to boost the time people are spending on the platform, the company is breaking into a totally new area: gaming.
TechCrunch has learned and confirmed that LinkedIn is working on a new games experience. It will be doing so by tapping into the same wave of puzzle-mania that helped simple games like Wordle find viral success and millions of players. Three early efforts are games called “Queens”, “Inference” and “Crossclimb.”
App researchers have started to find code that points to the work LinkedIn is doing. One of them, Nima Owji, said that one idea LinkedIn appears to be experimenting with involves player scores being organised by places of work, with companies getting “ranked” by those scores.
The advent of AI has ushered in transformative advancements across countless industries. Yet for all its benefits, this technology also has a downside. One of the major challenges AI brings is the amount of energy required to power the GPUs that train large-scale AI models. Computing hardware needs significant maintenance and upkeep, as well as uninterruptible power supplies and cooling fans.
One study found that training some popular AI models can produce about 626,000 pounds of carbon dioxide, the rough equivalent of 300 cross-country flights in the U.S. A single data center can require enough electricity to power 50,000 homes. If this energy comes from fossil fuels, that can mean a huge carbon footprint. Already the carbon footprint of the cloud as a whole has surpassed that of the airline industry.
As the founder of an AI-driven company in the blockchain and cryptocurrency industry, I am acutely aware of the environmental impact of our business. Here are a few ways we are trying to reduce that effect.
There is a lot we can learn about social media’s unregulated evolution over the past decade that directly applies to AI companies and technologies. These lessons can help us avoid making the same mistakes with AI that we did with social media.
In particular, five fundamental attributes of social media have harmed society. AI also has those attributes. Note that they are not intrinsically evil. They are all double-edged swords, with the potential to do either good or ill. The danger comes from who wields the sword, and in what direction it is swung. This has been true for social media, and it will similarly hold true for AI. In both cases, the solution lies in limits on the technology’s use.
The role advertising plays in the internet arose more by accident than anything else. When commercialization first came to the internet, there was no easy way for users to make micropayments to do things like viewing a web page. Moreover, users were accustomed to free access and wouldn’t accept subscription models for services. Advertising was the obvious business model, if never the best one. And it’s the model that social media also relies on, which leads it to prioritize engagement over anything else.
Let’s be honest – we’re all getting sick of seeing AI plastered over every tech product. A trend that will not be slowing down any time soon. A recent victim of this trend is the PC market, as AMD, Intel, Microsoft, and Qualcomm have been talking about AI PCs for the last year or so. Microsoft will be hosting an event on March 21st that is titled The New Era of Work. AMD, Intel, and Qualcomm will have dueling keynotes for their respective CEOs at Computex in Taipei, Taiwan. Be prepared for a flood of AI PCs this year.
In all honesty, Tirias Research has been a promoter of AI processing as the next big wave of computing – using trained data to better process predictive models and user interfaces. The use of AI processing has made major improvements to such PC tasks as voice recognition, video upscaling, video call optimization, microphone noise reduction, and power/battery management. The role of Large Language Models (LLMs) to build AI that can generate novel material/content from text prompts (Generative AI or just GenAI) has unleased another level of applications for AI. With GenAI, some tasks such as image development, creative and business writing, chatbot assistants, and now even video creation are possible with minimal user input. But to date, GenAI has run in cloud datacenters with some limited client device examples. The processing requirements and the power requirements to run the ever-increasing demand for GenAI is threatening to break cloud data centers.
DENVER—(BUSINESS WIRE)—Palantir Technologies Inc. (NYSE: PLTR) today announced that the Army Contracting Command – Aberdeen Proving Ground (ACC-APG) has awarded Palantir USG, Inc. — a wholly-owned subsidiary of Palantir Technologies Inc. — a prime agreement for the development and delivery of the Tactical Intelligence Targeting Access Node (TITAN) ground station system, the Army’s next-generation deep-sensing capability enabled by artificial intelligence and machine learning (AI/ML). The agreement, valued at $178.4 million, covers the development of 10 TITAN prototypes, including five Advanced and five Basic variants, as well as the integration of new critical technologies and the transition to fielding.
“This award demonstrates the Army’s leadership in acquiring and fielding the emerging technologies needed to bolster U.S. defense in this era of software-defined warfare. Building on Palantir’s years of experience bringing AI-enabled capabilities to warfighters, Palantir is now proud to deliver the Army’s first AI-defined vehicle” Post this
TITAN is a ground station that has access to Space, High Altitude, Aerial, and Terrestrial sensors to provide actionable targeting information for enhanced mission command and long range precision fires. Palantir’s TITAN solution is designed to maximize usability for Soldiers, incorporating tangible feedback and insights from Soldier touch points at every step of the development and configuration process. Building off Palantir’s prior work delivering AI capabilities for the warfighter, Palantir is deploying the Army’s first AI-defined vehicle.
We’re still years away from seeing physical quantum computers break into the market with any scale and reliability, but don’t give up on deep tech just yet. The market for high-level quantum computer science — which applies quantum principles to manage complex computations in areas like finance and artificial intelligence — appears to be quickening its pace.
In the latest development, a startup out of San Sebastian, Spain, called Multiverse Computing has raised €25 million (or $27 million) in an equity funding round led by Columbus Venture Partners. The funding values the startup at €100 million ($108 million), and it will be used in two main areas. The startup plans to continue building out its existing business working with startups in verticals like manufacturing and finance, and it wants to forge new efforts to work more closely with AI companies building and operating large language models.
In both cases, the pitch is the same, said CEO Enrique Lizaso Olmos: “optimization.”
Under the proposal, Lockheed would pay $1 per share of Terran Orbital stock it does not currently own, valuing the company at a little under $200 million. Lockheed would pay more than $70 million to buy outstanding stock warrants and assume or repay $313 million in Terran Orbital debt.
“Terran represents an attractive opportunity for Lockheed Martin, and we are treating the potential Transaction as a strategic priority,” Lockheed stated in the letter. “Terran’s superior capabilities and business momentum align with one of Lockheed Martin Space’s strategic growth priorities and the Transaction would accelerate that strategy.”
Underlying the storm of hype and funding in the AI sector right now is a scarce resource: data, created by old-fashioned humans, that’s needed to train the huge models like ChatGPT and DALL-E that generate text and imagery.
That demand is causing all sorts of drama, from lawsuits by authors and news organizations that say their work was used by AI companies without their permission to the looming question of what happens when the internet fills up with AI-generated content and AI creators are forced to use that to train future AI.
And, of course, it’s also fueling new business deals as AI developers rush to lock down repositories of human-generated work that they can use to train their AI systems. Look no further than this wild scoop from Bloomberg: that an undisclosed AI outfit has struck a deal to pay Reddit $60 million per year for access to its huge database of users’ posts — perhaps the surest sign yet that user data is the key commodity in the AI gold rush.
The Rebellionaire Road Rally has made its way down to Austin, TX. This time we’re joined by Farzad (@farzyness) to test out Tesla FSD v12 on the streets of the greater Austin area. This is part 2 of the journey with Farzad joining in the car adding helpful commentary.
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