Latest news with #GameDeveloper'sConference
Forbes
01-05-2025
- Forbes
AI Agents Playing Video Games Will Transform Future Robots
AI agents trained in video game environments are demonstrating a remarkable ability to transfer ... More skills to new challenges, potentially revolutionizing how we build real-world robots. Video games have played an important role in the development of AI. Many early demonstrations of machine learning involved teaching computers to play games. Eventually, Google Deepmind's mastery of the game Starcraft 2 was taken as proof that machines could now compete with us across many fields in which we were previously undisputed champions. Now, games are being used as a testbed for exploring some of the most exciting new areas in AI, including autonomous agents, real-world robots and perhaps even the quest for AGI. At this year's Game Developer's Conference, Google's DeepMind AI division demonstrated its research into what it calls Scalable Instructable Multiworld Agents (SIMA). The idea is to show that machines can navigate and learn inside the 3D worlds of video game environments. They can then use what they've learned to navigate entirely different worlds and tasks, all with their own rules, using whatever tools are available to them to solve problems. It might sound like child's play, but this research could dramatically impact the development of the agentic AI we'll use in our work and personal lives. So let's take a look at what it could mean, and whether it could even solve the ultimate AI challenge of creating machines capable of adapting to any situation, much like humans can. Video games provide a great environment for training AI because the variety of tasks and challenges is almost infinite. Importantly, the player usually solves these challenges using a standard set of tools, all accessed via the game controller. This corresponds well with the way AI agents tackle problems by choosing which tools to use from a pre-defined selection. Game worlds also provide safe, observable and scalable environments where the effects of subtle changes to variables or behavior can be explored at little real-world cost. DeepMind's SIMAs were trained across nine different video game environments, taken from popular games including No Man's Sky, Valheim and Goat Simulator. The agents were given the ability to interact and control the games using natural language commands like 'pick up the key' or 'move to the blue building.' Among the standout findings, the research showed that the agents are highly effective at transferable learning—taking what they learn in one game and using it to get better at another. This was backed up by observations that agents trained to play eight of the nine games performed better at the one game they were untrained on than specialized agents solely trained on the one game. This dynamic learning ability will be critical in a world where agents are working alongside us, helping us explore, interpret and understand messy real-world problems and situations. But what about looking a little further ahead, to a time when it's commonplace for robots to help us out with physical tasks as well as digital ones? The development of real-world robots that carry out physical tasks has accelerated in the last decade, hand-in-hand with the evolution of AI. However, they are still generally only used by large businesses due to the high cost of training them for specialist roles. Using virtual and video game environments could dramatically lower this cost. The theory is that transferable learning will enable physical robots to use their hands, arms or whatever tools they have to tackle many physical challenges, even if they haven't come across them before. For example, a robot that effectively learns how to use its hands to work in a warehouse might also learn how to use them to build a house. Before it released ChatGPT, OpenAI demonstrated research in this field. Dactyl is a robotic hand, trained in virtual simulated environments, that learned how to solve a Rubik's Cube. This was one of the first demonstrations of the potential of transferring skills learned in virtual environments to complex physical-world tasks. More recently, Nvidia has developed its Isaac platform expressly for the purpose of training robots to 'learn to learn' how to carry out real-world tasks inside virtual environments. Today, physical AI-assisted robots are put to work in warehouse roles, agriculture, healthcare, deliveries, and many other jobs. In most cases, however, these robots are still doing tasks they were specifically trained for—at enormous expense by companies with very deep pockets. But new models of 'affordable' robots are on the horizon. Tesla plans to manufacture thousands of its Optimus robots this year and assign many of them to work in its factories. And Chinese robotics developer Unitree recently unveiled a $16,000 humanoid robot that can turn its hand to many tasks. With the price of robots falling and their AI brains becoming more powerful by the day, walking, talking humanoid robots could be stepping out of science fiction into everyday reality sooner than we think. Almost 30 years ago, machines scored their first big win over humans by defeating Gary Kasparov at Chess. Few would have predicted then that a computer would exist that could beat world champions not just at one game, but at any game. This ability to 'generalize' information by taking knowledge from one task and using it to solve an entirely different one is traditionally exclusive to humans, but that could be changing. All of this will be hugely interesting to those chasing the holy grail of AI development, artificial general intelligence (AGI). Evidence that agents like DeepMind's SIMAs are able to transfer learning from one virtual game environment to another suggests they may be developing some of the qualities needed for AGI. It demonstrates that they are progressively building competencies that can be applied to solving future problems. Google, along with OpenAI, Anthropic and Microsoft, have all stated that developing AGI is their eventual goal, and it's clearly the logical endpoint of the current focus on agentic intelligence. With video games, could another part of the puzzle be in place?
Yahoo
14-03-2025
- Business
- Yahoo
Honeywell's Planned Spinoff and What It Means Amid Macro Volatility
March came in like a lion, much to the bears' delight. The S&P 500 plunged from its February 19 high on the heels of stern tariff talk and phrases like a little bit of an adjustment period from President Trump and the economy entering a detox period, as Treasury Secretary Bessent said last week.[1] While tariffs were certainly a cornerstone of Trump's 2024 campaign, the assumption was that his other pro-business policiesloosening regulation, lowering taxes, and filling his cabinet with free-market advocateswould overshadow any negative impacts from import duties. Moreover, the president going after Mexico, Canada, and Europe so aggressively was not anticipated, as China was generally seen as the primary trade-war enemy. Warning! GuruFocus has detected 3 Warning Sign with HON. The political chess game has seemingly never been so intertwined with markets. Investors have come to expect daily updates from the White House on tariff tweaks, while members of Trump's cabinet make news in TV interviews, ultimately driving price action. Coming into this week, stocks had been working lower, led by losses among the Magnificent Seven. Monday's steep selloff included a VIX spike to almost 30 as Tesla (TSLA) had its worst session since September 2020, at one point falling 56% from its all-time high less than three months ago. NVIDIA (NVDA) was off by more than 30% from its peak, and the other Mag 7 stocks were in drawdowns of 18% or more (sans Apple (AAPL)) last Monday night. It has the feel of both late 2018 and the first half of 2022 all over again. For some once-high-flying-momentum stocks, you might even draw parallels to February-March 2020 in terms of the speed and magnitude of losses. 2025 has underscored the value of going global, though. Low-P/E nations like Germany, Spain, Italy, and France have posted impressive gains year to date. As of Tuesday, the euro (EUR) trades at $1.09 against the greenback (USD), and fiscal expansion is now seen in the Euro Area while the US perhaps undergoes austerity, care of DOGE amongst other factors. The macro backdrop is stark. Earnings season is over, key macro data is on tap, and the March Fed meeting comes closer into view. Conference season is also activewe'll see if some shine returns to the AI trade next week at NVIDIA's GTC AI event and Game Developer's Conference (anything to distract investors from tariff chatter). With so much policy uncertainty, maybe the best thing for a CEO to do is just focus on their business and maximizing shareholder value rather than trying to predict tariff policy. In a CNBC interview last week, Brown-Forman CEO, Lawson Whiting, told Carl Quintanilla and Sara Eisen, Look, I don't know any more than you all know. That's what's difficult about this... Every day it seems like the story changes.[2] One way to potentially boost value is by re-jiggering the corporate structure. A spinoff happens when a parent company separates a business unit into a standalone entity, and it commonly involves distributing shares of a new company to existing shareholders. Spins are strategic moves to boost total value, allowing the new firm to focus on its specialization, and hopefully unlock hidden value. The parent company may benefit similarly as it can return to its roots. We've seen successful spinoffs in recent years. The most prominent being General Electric when it spun out into three businesses: GE Aerospace (NYSE:GE), GE Healthcare (GEHC), and GE Vernova (GEV).[3] GE Aerospace, the parent, has performed very well since the spinoff initiatives began some three years ago, soaring more than 400% from its September 2022 low to its high last month. GEHC steadily rallied from its December 2022 IPO through today, returning better than 40%. The wild child is GE Vernova, an energy-focused firm in the Industrials sector, which had more than doubled in its first 10 months of trading, before dropping from $447 in late January (after China's DeepSeek AI announcement)[4] to $270 earlier this week. Kellanova (K), Johnson & Johnson (JNJ), Baxter International (BAX), Danaher (DHR), and 3M (MMM) have all completed spins in the last three years. The latest blue chip to try its hand at uncovering shareholder value via this corporation action is Honeywell (NASDAQ:HON). Like GE, Honeywell is a conglomerate in the Industrials sector. According to Wall Street Horizon data, the Charlotte-based $139 billion market cap company intends to split into three entities: Honeywell Automation, Honeywell Aerospace, and an already-in-motion spinoff of its Advanced Materials division. It aims to streamline operations and sharpen its focus, increasing shareholder value. On February 6, Honeywell announced its intent to separate Automation and Aerospace. The move, according to the firm, enables the creation of three industry-leading companies. Per the press release, Honeywell Automation will be a pure play automation leader with global scale and a vast installed base and Honeywell Aerospace will be a premier technology and systems provider enabling the future of aviation globally. Advanced Materials, previously announced to be spun, will aim to be a leading provider of sustainability-focused specialty chemicals and materials. The separation of Automation and Aerospace is to be completed in the second half of 2026.[5] Honeywell hopes for a sweeter time ahead considering that its shares have underperformed in both the Industrials sector and S&P 500 since late 2022. The stock has been about flat since the bull market's early innings, losing more than 30 percentage points to its sector and the US large cap index. It's difficult to predict how the rest of the year unfolds, but investors should be on the lookout for strategic corporate actions that can work no matter what goes on policy-wise. Spinoffs have shown to be a potentially lucrative tool when used effectively. The focus spinoffs can deliver, and ensuing shareholder returns, could be quite appealing as the macro path turns rockier. 1 REMARKS BY PRESIDENT TRUMP IN JOINT ADDRESS TO CONGRESS, The White House, March 6, 2025, Brown-Forman Posts Q3 EPS Beat, BlueSky, Carl Quintanilla, March 6, 2025, GE Board of Directors Approves Spin-Off of GE Vernova; GE Vernova and GE Aerospace to Launch April 2, 2024, GE Vernova Inc. (GEV) Stock Drops 15% Amid DeepSeek AI Concerns, TD Cowen Maintains Buy' Rating Despite Lower Electricity Demand Fears, Yahoo Finance, Ghazal Ahmen, January 29, 2025, HONEYWELL ANNOUNCES INTENT TO SEPARATE AUTOMATION AND AEROSPACE, ENABLING THE CREATION OF THREE INDUSTRY-LEADING COMPANIES, PR Newswires, Honeywell, February 6, 2025, Copyright 2025 Wall Street Horizon, Inc. All rights reserved. Do not copy, distribute, sell or modify this document without Wall Street Horizon's prior written consent. This information is provided for information purposes only. Neither TMX Group Limited nor any of its affiliated companies guarantees the completeness of the information contained in this publication, and we are not responsible for any errors or omissions in or your use of, or reliance on, the information. This publication is not intended to provide legal, accounting, tax, investment, financial or other advice and should not be relied upon for such advice. The information provided is not an invitation to purchase securities, including any listed on Toronto Stock Exchange and/or TSX Venture Exchange. TMX Group and its affiliated companies do not endorse or recommend any securities referenced in this publication. This publication shall not constitute an offer to sell or the solicitation of an offer to buy, nor may there be any sale of any securities in any state or jurisdiction in which such offer, solicitation or sale would be unlawful prior to registration or qualification under the securities laws of any such state or jurisdiction. TMX, the TMX design, TMX Group, Toronto Stock Exchange, TSX, and TSX Venture Exchange are the trademarks of TSX Inc. and are used under license. Wall Street Horizon is the trademark of Wall Street Horizon, Inc. All other trademarks used in this publication are the property of their respective owners. This article first appeared on GuruFocus. Sign in to access your portfolio
