Latest news with #Joule
The Verge
4 days ago
- Business
- The Verge
AI could consume more power than Bitcoin by the end of 2025
AI could soon surpass Bitcoin mining in energy consumption, according to a new analysis that concludes artificial intelligence could use close to half of all the electricity consumed by data centers globally by the end of 2025. The estimates come from Alex de Vries-Gao, a PhD candidate at Vrije Universiteit Amsterdam Institute for Environmental Studies who has tracked cryptocurrencies' electricity consumption and environmental impact in previous research and on his website Digiconomist. He published his latest commentary on AI's growing electricity demand last week in the journal Joule. AI already accounts for up to a fifth of the electricity that data centers use, according to de Vries-Gao. It's a tricky number to pin down without big tech companies sharing data specifically on how much energy their AI models consume. De Vries-Gao had to make projections based on the supply chain for specialized computer chips used for AI. He and other researchers trying to understand AI's energy consumption have found, however, that its appetite is growing despite efficiency gains — and at a fast enough clip to warrant more scrutiny. 'Oh boy, here we go.' With alternative cryptocurrencies to Bitcoin — namely Ethereum — moving to less energy-intensive technologies, de Vries-Gao says he figured he was about to hang up his hat. And then 'ChatGPT happened,' he tells The Verge. 'I was like, Oh boy, here we go. This is another usually energy-intensive technology, especially in extremely competitive markets.' There are a couple key parallels he sees. First is a mindset of 'bigger is better.' 'We see these big tech [companies] constantly boosting the size of their models, trying to have the very best model out there, but in the meanwhile, of course, also boosting the resource demands of those models,' he says. That chase has led to a boom in new data centers for AI, particularly in the US, where there are more data centers than in any other country. Energy companies plan to build out new gas-fired power plants and nuclear reactors to meet growing electricity demand from AI. Sudden spikes in electricity demand can stress power grids and derail efforts to switch to cleaner sources of energy, problems similarly posed by new crypto mines that are essentially like data centers used to validate blockchain transactions. The other parallel de Vries-Gao sees with his previous work on crypto mining is how hard it can be to suss out how much energy these technologies are actually using and their environmental impact. To be sure, many major tech companies developing AI tools have set climate goals and include their greenhouse gas emissions in annual sustainability reports. That's how we know that both Google 's and Microsoft 's carbon footprints have grown in recent years as they focus on AI. But companies usually don't break down the data to show what's attributable to AI specifically. To figure this out, de Vries-Gao used what he calls a 'triangulation' technique. He turned to publicly available device details, analyst estimates, and companies' earnings calls to estimate hardware production for AI and how much energy that hardware will likely use. Taiwan Semiconductor Manufacturing Company (TSMC), which fabricates AI chips for other companies including Nvidia and AMD, saw its production capacity for packaged chips used for AI more than double between 2023 and 2024. After calculating how much specialized AI equipment can be produced, de Vries-Gao compared that to information about how much electricity these devices consume. Last year, they likely burned through as much electricity as de Vries-Gao's home country of the Netherlands, he found. He expects that number to grow closer to a country as large as the UK by the end of 2025, with power demand for AI reaching 23GW. Last week, a separate report from consulting firm ICF forecasts a 25 percent rise in electricity demand in the US by the end of the decade thanks in large part to AI, traditional data centers, and Bitcoin mining. It's still really hard to make blanket predictions about AI's energy consumption and the resulting environmental impact — a point laid out clearly in a deeply reported article published in MIT Technology Review last week with support from the Tarbell Center for AI Journalism. A person using AI tools to promote a fundraiser might create nearly twice as much carbon pollution if their queries were answered by data centers in West Virginia than in California, as an example. Energy intensity and emissions depend on a range of factors including the types of queries made, the size of the models answering those queries, and the share of renewables and fossil fuels on the local power grid feeding the data center. It's a mystery that could be solved if tech companies were more transparent It's a mystery that could be solved if tech companies were more transparent about AI in their sustainability reporting. 'The crazy amount of steps that you have to go through to be able to put any number at all on this, I think this is really absurd,' de Vries-Gao says. 'It shouldn't be this ridiculously hard. But sadly, it is.' Looking further into the future, there's even more uncertainty when it comes to whether energy efficiency gains will eventually flatten out electricity demand. DeepSeek made a splash earlier this year when it said that its AI model could use a fraction of the electricity that Meta's Llama 3.1 model does — raising questions about whether tech companies really need to be such energy hogs in order to make advances in AI. The question is whether they'll prioritize building more efficient models and abandon the 'bigger is better' approach of simply throwing more data and computing power at their AI ambitions. When Ethereum transitioned to a far more energy efficient strategy for validating transactions than Bitcoin mining, its electricity consumption suddenly dropped by 99.988 percent. Environmental advocates have pressured other blockchain networks to follow suit. But others — namely Bitcoin miners — are reluctant to abandon investments they've already made in existing hardware (nor give up other ideological arguments for sticking with old habits). There's also the risk of Jevons paradox with AI, that more efficient models will still gobble up increasing amounts of electricity because people just start to use the technology more. Either way, it'll be hard to manage the issue without measuring it first.
Yahoo
5 days ago
- Business
- Yahoo
SAP and Microsoft broaden cloud ERP alliance
This story was originally published on CIO Dive. To receive daily news and insights, subscribe to our free daily CIO Dive newsletter. SAP expanded its partnership with Microsoft to help drive enterprise adoption of the ERP provider's Business Suite bundles for finance, supply chain, human resources, procurement and customer experience functions, the two companies said Tuesday. The joint migration acceleration initiative complements extensive platform integration plans unveiled along with the Business Suite offerings last week during SAP's annual Sapphire conference. The integrations announced May 20 connect SAP's Joule AI assistant with the Microsoft 365 suite of productivity tools, including Copilot, Teams, Outlook and Word. Microsoft also extended its Sentra, Defender and Entra security tools across SAP's cloud ERP and aims to launch SAP Business Data Cloud and SAP Databricks on Azure analytics services later this year. SAP is counting on technology partners to guide customers to its S/4HANA cloud-based ERP as the company prepares to terminate mainstream support for on-premises ERP Central Component deployments in 2027. 'By combining forces, we provide partners with proven frameworks, shared resources, and scalable tools that address complex challenges,' Karl Fahrbach, chief partner officer of SAP, said in the Tuesday announcement. The bundled offerings are designed to ease migrations by targeting function-specific business processes with traditional ERP capabilities in combination with data pipeline, analytics and AI services. While Microsoft is the first hyperscaler to offer the Business Suite Accelerator program, SAP recently expanded existing pacts with AWS and Google Cloud to ease the flow of ERP data across clouds. AWS and SAP launched a generative AI development initiative to help Accenture, Deloitte and other ecosystem partners build agentic tools using ERP data and the hyperscaler's Bedrock platform, the companies announced on May 20. Initial use cases include identifying financial anomalies in real time and mitigating supply chain disruptions, according to SAP CTO and Chief AI Officer Philipp Herzig. In addition to integrating the Databricks-powered Business Data Cloud on Azure, SAP connected the data pipeline to Google Cloud's BigQuery data warehouse to bring together data stored in ERP and third-party repositories. SAP Business Data Cloud will be deployed in three Google Cloud regions in later this year, according to a May 20 announcement. SAP was among the first cadre of providers to sign on to Google Cloud's Agent2Agent open protocol for multi-agent AI orchestration in April. The two companies gave SAP customers access to Google's Gemini family of large language models through SAP Business Technology Platform's generative AI hub and opened SAP data to the hyperscaler's Agentspace tool-building platform earlier this month. 'Our objective is to enable all enterprises to streamline data integration and data science, enhance their analytical workflows, and accelerate their transformation into an AI-driven enterprise,' the companies said in the announcement.
Yahoo
6 days ago
- Business
- Yahoo
Salesforce reinforces its AI cloud with $8B Informatica acquisition
This story was originally published on CIO Dive. To receive daily news and insights, subscribe to our free daily CIO Dive newsletter. Salesforce agreed to purchase Informatica for approximately $8 billion Tuesday in a move designed to strengthen its cloud-based data and AI capabilities. 'Together, Salesforce and Informatica will create the most complete, agent-ready data platform in the industry,' Salesforce Chair and CEO Marc Benioff said in the announcement. The CRM provider will integrate Informatica's data governance and management services with its Data Cloud warehouse, MuleSoft hybrid interface and Tableau analytics platforms to build out its Agentforce enterprise AI automation hub, the company said. 'This proposed acquisition will be a key enabler for Salesforce's next phase of AI-driven growth — and we will move quickly to integrate their capabilities and unlock synergies on a fast timeline,' said Robin Washington, president and chief operating and financial officer at Salesforce. The transaction has approval from both companies' boards and is expected to close early in Salesforce's fiscal year 2027, which begins in February. As the agent deployment race heats up, major enterprise software providers are reinforcing their data foundations to provide autonomous AI tools with fuel for insights and action. The Informatica acquisition follows a flurry of agentic-related moves in the industry. SAP forged a data pipeline alliance with Databricks in February to amplify its Joule copilot's agentic capabilities. The enterprise software giant's Business Data Cloud platform connects ERP data with outside data repositories to put additional muscle behind machine learning, AI and agentic applications. In January, ServiceNow rolled out its AI Agent Orchestrator command center and promised to deliver thousands of pre-built agentic tools to its platform. The enterprise software company added the agent-focused Workflow Data Network multiplatform integration to its suite and purchased data governance and management start-up for an undisclosed sum in early May. 'ServiceNow is working with some of the largest companies in the world to eliminate data silos head‑on, enabling enterprises to accelerate AI adoption at scale,' said Gaurav Rewari, SVP and general manager of data and analytics products at ServiceNow, in the May announcement. Salesforce has already seen returns on its investements in agentic capabilities. After reporting 120% year-over-year revenue growth for its Data Cloud and AI segment, Benioff dubbed the three-month period ending on Jan. 31 as 'the quarter of Agentforce' during a February earnings call. Earlier this month, the company expanded its army of agent-focused AI models and added automation software startup to its growing M&A portfolio. While the terms of the deal were undisclosed, Salesforce is no stranger to multibillion-dollar acquisitions. The Informatica deal is dwarfed by two prior Salesforce acquisitions — nearly $28 billion for Slack in 2020 and almost $16 billion for Tableau in 2019. The company purchased MuleSoft for $6.5 billion in 2018.
Yahoo
7 days ago
- Business
- Yahoo
SAP SE (SAP)'s Strategic Pivot Drives Optimism – JPMorgan Reaffirms Overweight Rating
We recently published a list of . In this article, we are going to take a look at where SAP SE (NYSE:SAP) stands against other AI stocks on Wall Street's radar. SAP SE (NYSE:SAP) is a leader in ERP software that leverages artificial intelligence to enhance its enterprise resource planning (ERP) solutions. On May 23, JPMorgan analyst Toby Ogg reiterated an 'Overweight' rating and EUR290.00 price target on the stock. The reiteration follows SAP's Sapphire Conference in Orlando, where the company demonstrated a strategic pivot, focusing on suite-as-a-service applications, its Business Data Cloud, and artificial intelligence initiatives such as Joule & AI Agents. Ogg also pointed toward early interest in SAP's Business Data Cloud. Moreover, discussions with key SAP partners revealed eagerness for the company's integration with Databricks, a partnership that allows companies to prepare enterprise data for AI capabilities. The firm believes that these initiatives are seen as growth drivers and aren't fully reflected in consensus views, offering potential upside. A data centre room with cloud technology, illustrating the enterprise application software services. SAP's CFO, Dominik Asam, talked about some challenges impacting cash conversion in 2026, but at the same time, also noted the sustainability of SAP's growth. Overall, the firm holds a positive view about the company's revenue growth through 2027. This supports a mid-term investment case for the stock. Overall, SAP ranks 10th on our list of AI stocks on Wall Street's radar. While we acknowledge the potential of SAP as an investment, our conviction lies in the belief that some AI stocks hold greater promise for delivering higher returns and have limited downside risk. If you are looking for an AI stock that is more promising than SAP and that has 100x upside potential, check out our report about this cheapest AI stock. READ NEXT: and . Disclosure: None. This article is originally published at Insider Monkey. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Channel Post MEA
7 days ago
- Business
- Channel Post MEA
SAP Unveils New AI Features For Enterprise Applications
At its annual SAP Sapphire conference, SAP unveiled innovations and partnerships that put the power of Business AI in every user's hands, revolutionising the way work gets done. From a virtually omnipresent Joule assistant to an expanded network of Joule Agents that work across systems and lines of business, SAP heralds a new era that democratises access to Business AI and can drive productivity gains of up to 30%. 'SAP combines the world's most powerful suite of business applications with uniquely rich data and the latest AI innovations to create a flywheel of customer value,' said SAP CEO Christian Klein. 'With the expansion of Joule, our partnerships with leading AI pioneers, and advancements in SAP Business Data Cloud, we're delivering on the promise of Business AI as we drive digital transformations that help customers thrive in an increasingly unpredictable world.' AI that boosts productivity Joule can accompany business users throughout their day, in and out of the SAP application universe, to find data, surface real-time insights and streamline workflows. Joule's new ubiquity includes an action bar powered by WalkMe that studies user behaviour across applications, turning the assistant into an always-available, proactive AI that can anticipate users' needs before they arise — always adhering to SAP's strict ethical AI guidelines. A collaboration with Perplexity, an AI-powered answer engine company, enhances Joule's ability to draw on structured and unstructured data to solve complex business problems. Powered by Perplexity and the SAP Knowledge Graph, Joule now instantly answers questions with structured, visual answers — such as charts and graphs — grounded in real-time business data within SAP workflows. SAP also unveiled an expanded library of Joule Agents that reimagine business processes and workflows from the ground up. Fuelled by the world's most powerful real-time business data and orchestrated by Joule, these AI agents work across systems and lines of business to anticipate, adapt and act autonomously so organisations can stay agile in a rapidly changing world. Leading companies reap business AI benefits Several leading brands showcased how SAP Business AI has enhanced their operations. Global brewer Heineken has introduced an internal artificial intelligence (AI) chatbot, 'Hoppy,' to enhance business processes and offer real-time data access. The AI-driven chatbot runs on SAP Business Technology Platform (SAP BTP) and represents a significant leap forward in Heineken's commitment to streamlining internal processes and empowering its workforce. By leveraging advanced natural language processing with data across multiple systems, Hoppy eliminates the need for time-consuming manual searches and allows business users to focus on more strategic and impactful tasks. Since Hoppy was introduced within the company's collaboration platforms, Heineken has seen the time knowledge workers need to retrieve information fall to 1 minute from 15 minutes. With SAP Business AI capabilities at Hoppy's core, Heineken also is exploring automating repetitive tasks to enhance business processes and streamline communications and decision-making. Competitive gaming organisation Team Liquid is tapping into Joule Agents for instant access to game statistics, player performance trends and strategic comparisons using natural language. Unlike traditional AI models, AI agents are designed to perceive their environment, set goals and take actions autonomously to achieve those objectives. Team Liquid runs its data analysis through its 'Next Level Esports Center' dashboard, built entirely on SAP Business Technology Platform. Team Liquid's analysts rely on the dashboard to equip coaches and players with insights about upcoming opponents, managing high-pressure situations under short turnaround times and frequent data requests between games. Instead of relying solely on technical analysts, players, coaches and marketing teams can ask the Joule copilot for player or team insights, tapping into more than 1.6 TB of data from 10 million games to find the right answer and uncover strategic advantages. This shift eliminates the need for manual data retrieval, empowering diverse users to make data-driven decisions at game speed. Data that drives smarter decisions SAP also introduced new intelligent applications in SAP Business Data Cloud, each built for a specific line of business. These applications can continuously learn, simulate outcomes and guide actions using business-critical data, detecting changes to optimise processes, anticipate needs, and collaborate with both human and artificial thinkers to drive meaningful impact. The People Intelligence application, for instance, optimises team performance by transforming people and skills data into workforce insights and AI-driven recommendations. Additionally, SAP and Palantir are partnering to facilitate joint customers' cloud migration journey and modernisation programs. Seamless connectivity between Palantir and SAP Business Data Cloud will enable customers to build a harmonised data foundation across their enterprise landscape. Together the companies will responsibly deliver essential outcomes and support customers to quickly adapt to changes and disruptions. 0 0
