Top AI Tech Trend, Coheres' Embed 3 & Runways' Character Animation

Gartner Names Agentic AI Top Tech Trend for 2025 

"Today's AI models perform tasks such as generating text, but these are 'prompted' — the AI isn't acting by itself. That is about to change with agentic AI, or AI with agency. By 2028, 33% of enterprise software applications will include agentic AI, up from less than 1% in 2024, enabling 15% of day-to-day work decisions to be made autonomously." Tom Coshow, senior director analyst, weighed in: "Organizations have long wanted to promote high-performing teams, improve cross-functional collaboration and coordinate issues across team networks. Agentic AI has the potential to perform as a highly competent teammate by providing insights from derivative events that are often not visible to human teammates." 

Genmo launches Mochi 1 Text-to-Video Generation Model, But Server Crashes Within Hours

Share On October 22, Genmo, the AI based video generating platform, released Mochi 1, a new state-of-the-art open-source text-to-video generation model. It can generate high quality videos with mere text prompts. 

AI to amplify India's Digital Public Infrastructure and boost inclusion ...

Artificial intelligence can further amplify India's Digital Public Infrastructure (DPI) and accelerate inclusion across the nation, said Nandan Nilekani, non-executive chairman, Infosys, at the ...

Microsoft and OpenAI are offering $10 million to News outlets to use AI 

Microsoft and OpenAI want journalists to leverage AI tools in newsrooms, and they are ready to spend up to $10 million to support the cause. Discussion:

The collaboration between Microsoft, OpenAI, and news outlets to integrate AI tools into newsrooms with a $10 million investment marks a significant step towards AI-driven journalism. While AI can enhance research and reporting processes, concerns about copyright infringement and reliance on AI-generated content remain. This initiative reflects a growing trend of tech companies supporting media innovation. The use of AI in newsrooms can streamline tasks like transcription and summarization, improving efficiency. However, the balance between AI assistance and human journalistic integrity is crucial. As AI continues to shape various industries, including journalism, ethical considerations and proper training for journalists on AI integration will be essential to maintain quality and credibility in news reporting. This partnership sets a precedent for future collaborations between technology firms and media organizations to harness AI's potential responsibly and effectively.

AI Sets Shiba Inu (SHIB) Price For November 2024

November is upon us, and the cryptocurrency market is gearing up for potential price changes. Shiba Inu (SHIB), one of the leading meme coins in the space, has had a modest October with occasional price spikes. November is ushering in hopes for the market, especially regarding Bitcoin and Shiba Inu performing their best in price ascent. Here’s how SHIB may perform next month. Also Read: Tesla Q3 Earnings To Make TSLA A Magnificent 7 Stock? October ushered in some major updates for the Shiba Inu ecosystem. For instance, SHIB gained massive momentum after its DAO announcement, which was first recently disclosed by Lucie, SHIB’s marketing dev. Dubbed the SHIB Doggy DAO, this development indicates increased community support and hopes to deliver a holistic web3 experience to SHIB community members. “The SHIB Doggy DAO Foundation will legally wrap around the DAO, ensuring that the decisions made by the community are properly executed. It will manage assets like the Doggy Treasury and prevent any future misallocations, providing transparency and security. This move demonstrates to the world that Shib isn’t just another project—it’s a serious player with a long-term vision.” At the same time, October also brought significant price momentum for SHIB due to Bitcoin’s price upswing. As Bitcoin claimed the $67 mark, the majority of the investors were noted flocking around SHIB and Doge, which helped the tokens gain modest price upticks. In addition to this, as the crowd anticipates Bitcoin’s ascent to $70K, the development can shift SHIB’s price in the process, helping it gain considerable market momentum. “With the crowd anticipating Bitcoin’s $70K breach soon, traders are doubling down on high leverage speculative meme coins, where their discussion rates are at their highest level in 5 months. Meanwhile, L2’s like arbitrum and optimism are being ignored. Speculative coins can certainly still pump a bit longer, but historical data shows that it pays to go where the crowd isn’t looking.” Also Read: Buy Jio Financial Shares: Revised Price Target 345: Analyst According to CoinCodex, Shiba Inu may note a modest price uptick this November 2024. The token may surge by 1% to hit a stable price level of $0.00001818. “According to our current Shiba Inu price prediction, the price of Shiba Inu is predicted to rise by 1.16%. It could reach $0.00001818 by November 22, 2024. Per our technical indicators, the current sentiment is bearish while the Fear & Greed Index is showing 71 (greed). Shiba Inu recorded 13/30 (43%) green days with 7.44% price volatility over the last 30 days. Based on the Shiba Inu forecast, it’s now a bad time to buy Shiba Inu.” Also Read: Bitcoin: Here’s What Elon Musk’s Tesla Is Doing With Its BTC Disclaimer: Our articles are NOT financial advice, we are not financial advisors. All investments are your own decisions. Please conduct your own research and seek advice from a licensed financial advisor.

Enhanced Coding with Claude 3.5 Haiku: Speed and Accuracy - Geeky Gadgets

Geeky Gadgets The Latest Technology News 1:45 pm October 23, 2024 By Julian Horsey Anthropic has this week updated it’s Claude 3.5 Haiku AI model refining its processing powers to offer a blend of speed, accuracy, and affordability that sets a new standard in the industry. It’s clear that Claude 3.5 Haiku is more than just an upgrade; With its unparalleled efficiency in handling complex coding tasks and multilingual processing, this model is poised to transform how we approach AI-powered applications. And the best part? It’s designed to be accessible to everyone, from individual developers to large enterprises, thanks to its cost-effective pricing strategy. So, if you’ve ever felt limited by the tools at your disposal, prepare to be inspired by the possibilities that 3.5 Haiku brings to the table. Anthropic’s Claude 3.5 Haiku represents a notable advancement in the field of language model technology. As the latest addition to the 3.5 Series, this model is engineered to be the fastest and most cost-effective option available, surpassing its predecessor, the 3.0 Haiku. Specifically designed to excel in coding tasks, Claude 3.5 Haiku sets new standards in the industry. For the same cost and similar speed as Claude 3 Haiku, Claude 3.5 Haiku improves across every skill set and surpasses Claude 3 Opus, the largest model in Anthropic’s previous generation, on many intelligence benchmarks. Pricing for Claude 3.5 Haiku starts at $0.25 per million input tokens and $1.25 per million output tokens, with up to 90% cost savings with prompt caching and 50% cost savings with the Message Batches API. To learn more, check out the pricing page. TL;DR Key Takeaways : Claude 3.5 Haiku offers substantial improvements in both speed and accuracy, crucial factors for efficient coding processes. The model handles complex tasks with minimal latency, making sure a highly responsive user experience. It has achieved outstanding results in various coding benchmarks, often outperforming other leading models in the field. Key performance enhancements include: The model’s versatility extends beyond coding, making it a valuable tool for a wide range of global applications. Its ability to handle multilingual tasks efficiently further enhances its utility across diverse industries and regions. A standout feature of Claude 3.5 Haiku is its cost-effectiveness. Priced at just 0.25 cents per million tokens, it offers a financially viable solution for users ranging from individual developers to large enterprises. The model provides additional value through: This pricing strategy aims to provide widespread access to access to innovative AI capabilities, allowing a broader range of users to use advanced language model technology in their projects and workflows. Uncover more insights about Language Model (LLM) in previous articles we have written. Claude 3.5 Haiku is designed for easy integration into existing systems. Initially available as a text-only model, it can be accessed through popular platforms such as: This availability assists seamless API integration, allowing users to incorporate the model into their current workflows with minimal disruption. While currently focused on text processing, future updates may expand its capabilities to include

Exploring Anthropic's Computer Use API: A New Era in AI

Anthropic has unveiled two new AI models and a Computer Use API, marking a significant leap forward in technological capabilities. These developments are poised to transform how you interact with digital tools, offering substantial enhancements in both performance and efficiency. Anthropic’s latest offering, the Sonnet 3.5 model, represents a major advancement in AI technology. This model brings notable improvements in coding and agentic tool use, setting new benchmarks in the field. Sonnet 3.5 demonstrates exceptional performance in Software Engineering (SWE) and Technical Agent Use (TAU) benchmarks, establishing itself as a frontrunner in AI capabilities.

Cohere Unveils Embed 3, a Multimodal Breakthrough for AI Search with Leading Text+Image Capabilities

Share Cohere today unveiled Embed 3, its most advanced multimodal AI model, which seamlessly integrates text and image embeddings within a unified latent space, setting new benchmarks for accuracy and performance in enterprise search and multilingual retrieval tasks. The model is capable of generating embeddings from both text and images enabling businesses to unlock valuable insights from their vast data, including complex reports, product catalogs, and design files, boosting workforce productivity. Embed 3 is now available on Cohere’s platform, Amazon SageMaker, and for private deployment in any VPC or on-premise environment. Embed 3 converts data into numerical representations within a unified vector space, allowing for accurate similarity comparisons across text and image data. This ensures balanced and highly relevant search results without bias toward one modality, setting it apart from other models. Discussion:

Cohere's unveiling of Embed 3 marks a significant advancement in AI search capabilities by seamlessly integrating text and image embeddings. This breakthrough not only enhances enterprise search accuracy and performance but also revolutionizes data-driven decision-making and customer experiences. The model's ability to support over 100 languages underscores its global relevance for diverse enterprises. Cohere's focus on developing practical large language models for business applications, rather than pursuing artificial general intelligence like some competitors, highlights a strategic niche in the AI market. The success and valuation of Cohere spotlight the growing demand for AI solutions tailored for enterprise needs. This trend signals a shift towards specialized AI applications that deliver tangible benefits across industries, emphasizing the importance of practical and scalable AI innovations in today's technology landscape.

Runway’s New Model Simplifies Character Animation for Creators

Share Runway, an NYC based AI video startup, announced Act-One, a new state-of-the-art tool for generating expressive character performances, inside Gen-3 Alpha. The access to Act One is currently limited. Act-One can generate compelling animations by just using video and voice performances as inputs. The tool reduces the reliance on traditional motion capture systems, making it simpler to bring characters to life in production workflows. 

Claude AI tests human-like computer use in public beta

If you're seeing this message, that means JavaScript has been disabled on your browser. Please enable JavaScript to make this website work. Contact · Help A member of The Business Times. Copyright © 2024 Tech in Asia. All Rights Reserved. Claude 3.5 Sonnet, the latest version of Claude AI, now includes a feature that allows it to use computers like humans. This capability is currently in public beta, enabling the AI to move a cursor, click on objects, and input text with a virtual keyboard. This development allows models to interact with computer software similarly to human users, adding to earlier advancements like logical reasoning and image understanding. Research for this capability involved training Claude to interpret and interact with screen images. The AI counts pixels to move the cursor, facilitating tasks that require clicking on specific areas. Testing showed that Claude could generalize its computer-use skills from limited training with basic software. 👀 See Also: OpenAI's Paris-based rival raises $640m at $6b valuation 🔗 Source: Anthropic 📅 Upcoming Events October 23 - 24, 2024 [🔥Selling fast!] Tech in Asia Conference Jakarta 2024 24 October 2024 Tech in Asia's Founders Meetup: Jakarta 14 November 2024 Tech in Asia's Founders Meetup: Philippines By signing up, I agree to Tech in Asia's Terms of Service and Privacy Policy. A member of The Business Times. Copyright © 2024 Tech in Asia. All Rights Reserved.

Meta is Up 350% Since 2022 as AI Plan Has it Outperforming Tech Titans

Despite its poor performance two years ago, Mark Zuckerberg’s Meta (META) is up nearly 350% since 2022, as its AI strategy has it outperforming some of the biggest titans in tech. Indeed, the company has come out ahead of behemoths like Apple (APPL) and Alphabet (GOOGL) as far as its gains in the last several years. That could be set to continue for the company, as its Q3 earnings report is nearing. It has continued to stay on the cutting edge, shifting with growing demand and pivoting with changing interests throughout the sector. The company most recently debuted its Orion augmented reality glasses, further solidifying that commitment to growth and expansion. Also Read: Meta Reintroduces Key Tech Feature as Stock Nears All-Time High The information technology sector has been a focal point for much of the last year. With Nvidia (NVDA) emerging amid a 190% stock surge, companies are looking to embrace the tech that resulted in such high demand for the chipmaker. Yet, only a few companies have been able to make that transition successfully. Microsoft (MSFT) has thrived, but some have stumbled. Yet one has shocked the market with its recent shift. Indeed, Meta is up 350% since 2022 as its embrace of AI has driven tremendous gains. Specifically, the company is up more than 560% since its low two years ago. Also Read: Meta Stock Target Gets Boost as Q3 Looks to Build Off 2024 Success Over the last 24 months, only Nvidia’s 1,052% gains outearn Meta. The biggest reason is due to a plethora of cost-cutting measures as well as AI integration strategies that reaffirmed its position amid cutting-edge entities within the industry. In July, Mack Zuckerberg assured the importance of artificial intelligence to the company’s future. During that month’s earnings call, he said, “Across Facebook and Instagram, advances in AI continue to improve the quality of recommendations and drive engagements.” “We keep finding that as we develop more general recommendation models, content recommendations get better period,” he added. Currently, most analysts have a buy rating on the stock. With its Q3 earnings around the corner, it could be set to increase after recently setting an all-time high stock price. Disclaimer: Our articles are NOT financial advice, we are not financial advisors. All investments are your own decisions. Please conduct your own research and seek advice from a licensed financial advisor.

VC funding for AI in 2024 to exceed last year’s $23bn 

Posted By: Euro Financial Review October 23, 2024 Venture capital funding for generative AI startups in 2024 is poised to exceed the records of 2023, according to a report by S&P Global. In the first three quarters of this year, GenAI startups secured over $20 billion, according to S&P Global Market Intelligence data. That puts 2024 on track to exceed the 2023 total of $22.7 billion. “As in the previous year, this year’s funding surge was significantly driven by billion-dollar mega-rounds from prominent players such as OpenAI LLC and Anthropic PBC,” said the report. “The second quarter was propelled by X.AI Corp.’s $6 billion funding deal, while the third quarter was led by Sam Altman’s OpenAI securing $6.6 billion. “The momentum will likely continue, with Anthropic, which already raised $8.8 billion, reportedly in discussions for another fundraising round. “The second and third quarters were equally strong and represented the highest quarterly funding total since the first quarter of 2023, which was marked by Microsoft Corp.’s $10 billion investment in OpenAI … “The competition in the frontier foundation model space is intense with new entrants this year such as Elon Musk’s X.AI and Ilya Sutskever’s Safe Superintelligence Inc., with the latter raising $1 billion. In the US and Europe, there are now at least six frontier foundation models to choose from and more are coming. “Investor interest in funding new ventures within the GenAI sector remains robust, particularly when led by experienced entrepreneurs. “However, building a foundation model from the ground up is capital intensive and the competitive landscape is daunting, as deep-pocketed tech juggernauts such as Alphabet Inc. and Meta Platforms Inc. have access to significantly greater resources than more focused startups. “Although many of these startups are incurring substantial cash burn, investors are optimistic about the pace of revenue growth and the opportunity if GenAI emerges as the next transformative technology platform. According to a report from Stripe Inc., cited by the Financial Times of London, GenAI companies reached $30 million in revenue quicker than similar companies in other technology shifts, including software as a service.” Companies competing in the foundation model arena are investing significantly to develop the next iteration of GenAI models to escape commoditization. Having the leading model will enable them to capture a substantial share of a rapidly expanding market, the ultimate size of which is impossible to predict. As the competition intensifies, some disheartened players will likely exit the race or consolidate. “This is a game of survival, if you are not early to build the moat around you, you are going to be left behind,” Arun Bharath, chief investment officer at Bel Air Investment Advisors, said in an interview with S&P Global Market intelligence. COPYRIGHT 2017 | EUROPEAN FINANCIAL REVIEW

From bootstrapping to a $665m cash acquisition: How Silo AI made it to ...

Sarlin points to deals like Microsoft’s acquisition of Inflection AI, founded by Mustafa Suleyman, ... With the news about AMD acquiring Silo AI in July 2024, the all-cash deal of $665m sounds small in comparison to the VC raises of some AI companies, like London-based self-driving car software company Wayve, which raised $1bn this year. But as Sarlin points out, you cannot compare apples with pears. ...

How AI is transforming venture building and venture capital | Saïd Business School

By Thomas Hellmann, Kutlu Kazanci and Mari Sako The Oxford Entrepreneurship Policy Roundtable (OXEPR) convened over 40 founders, angel investors, venture capitalists (VCs), senior executives, and academics to discuss the opportunities and challenges of building and investing in artificial intelligence (AI) ventures in Europe. The roundtable set out to understand the future of venture building and venture investing in light of the recent advances in AI. It posed and discussed the following five key questions: Roundtable participants emphasised two factors all AI startups require to be commercially viable. First, they must generate outstanding user experiences that build and maintain trust with their clients. Second, they must own some proprietary data to continuously improve consumer experiences and ensure client retention. AI models are developing at a rapid pace. Consequently, AI startups need to strategically position themselves not only against the current competition, but also against future improvements in AI models. This requires a high degree of fluidity and adaptability, because those who are not prepared for the rapid advancements risk being 'steamrolled' by larger incumbents, like OpenAI. Unlike previous generations of software companies, AI companies need to develop business models that deviate from the established 'Software as a Service' (SaaS) model. They need to design offerings around capabilities that are not only enabled by AI, but also constantly updated by the latest AI advances. Different from traditional SaaS systems, the long-term cost structures of AI systems require constant maintenance and improvements. While large language models (LLMs) led by US incumbents dominate, European opportunities lie in developing smaller models that can be curated with proprietary data sets. Examples include Retrieval Augmented Generation (RAG), edge implementations, and AI agents. Tailored AI solutions for specific industry needs and non-language-based AI applications also present significant opportunities. Large established companies, which are the main customers of B2B-oriented AI startups, are potentially considering the adoption of AI differently from the adoption of SaaS software. Inside these large enterprises, there is considerable debate about building AI capabilities internally versus buying it from third parties. They are looking for established software providers and startups that can offer data sets and capabilities beyond their internal capabilities. However, given the nature of the data and capabilities required to operate AI models, there is considerable reluctance to outsource to third-party companies. This makes it especially difficult for younger smaller startups, that unlike the large established software providers (including the tech giants), do not have any proven track record. The internal adoption of AI initiatives is largely determined by the most influential senior managers, who are not necessarily the most knowledgeable about the current and future risks and rewards of AI adoption. In principle, AI technologies also have the potential to empower middle managers. However, to realise their potential, organisations often need to redesign their structures and change their internal culture accordingly. One important unanswered question is whether established companies will continue to develop sufficient interest in acquiring AI startups, to generate the exits that VCs require to make their investment returns. Even

Cyera Acquires Trail Security for $162M as AI Fuels Cybersecurity M&A Surge

Cyera, a cybersecurity company, is acquiring the data loss prevention startup Trail Security for $162 million. This deal highlights how artificial intelligence (AI) is accelerating the need for growth through mergers and acquisitions (M&A). Trail Security, an Israel-based firm founded in 2023, has operated under the radar since its inception. The startup focuses on data loss prevention technologies, which protect sensitive information from cyberattacks. Before the acquisition, Trail Security raised $35 million from investors such as Lightspeed Ventures, CRV, and Cyberstarts. Yotam Segev, Cyera’s co-founder and CEO, noted that AI is intensifying the threat of cyberattacks, making M&A crucial for keeping pace with industry demands. He explained that M&A enables access to greater engineering capabilities. “Customers in the cybersecurity space today are looking for comprehensive platforms, and we aim to solve not just yesterday’s challenges but continue growing,” Segev added. Founded in 2021, Cyera utilizes AI to help companies manage their data infrastructure by providing tools to visualize, track, and protect where data is stored, accessed, and generated. The New York-based company recently tripled its valuation to $1.4 billion after raising $300 million in a Series C funding round in April, less than a year after its previous financing. This acquisition occurs during limited exit opportunities, including startup-to-startup M&A activity. According to PitchBook, 78 acquisitions have been completed this year, amounting to $2.8 billion in deals where startups were sold to other VC-backed companies. The broader VC exit market hit a five-quarter low in Q3, based on PitchBook-NVCA Venture Monitor data. Despite this, cybersecurity exits are beginning to show signs of recovery. In September, Mastercard acquired Recorded Future, a threat intelligence platform, for $2.65 billion, resulting in significant returns for investor Insight Partners. Optimism in cybersecurity remains high, even after a proposed deal between Google and cloud security company Wiz fell through in July. By ROBERT RITCH · Launched 5 months ago Manage finances and build wealth Ready for more? undefined subscriptions will be displayed on your profile (edit) Skip for now For your security, we need to re-authenticate you. Click the link we sent to , or click here to sign in.

Growth Capital Update: Q3 2024

Later-stage VC deals were the most common type of transaction in Q3, accounting for 38% of all deals completed and 44% of total funds invested. ... start-up that builds AI bots for process automation, automating end-to-end workflows, raised $24 million in a Series A funding round led by Benchmark in September. The Series A round came a year after 11x.ai raised $2 million seed capital in a round led by Project A Ventures. ... Founded in London in 2022, the company calls its AI ‘agents ...

Neysa Raises $30 Million to Expand AI Infrastructure

Mumbai: Neysa, a company providing AI acceleration cloud systems, has raised $30 million in Series A funding led by NTTVC, Z47, and Nexus Venture Partners. The funds will be used to expand its AI infrastructure and boost research and development. Launched in July 2024, Neysa’s platform, Velocis, is gaining customers from industries like media, digital services, and the public sector.

The Decline of Exits and VC Returns: A Focus on Early-Stage Investments - Development Corporate

Development Corporate Product Management and M&A. Musings of a reformed private equity operator The venture capital (VC) industry has seen a notable shift over recent years, particularly in the areas of exits and returns. This decline is especially pronounced in early-stage investments, where the market has seen a significant downturn in exit opportunities and corresponding returns. This blog post explores the current state of the VC ecosystem, with a particular focus on early-stage investments, and delves into the challenges contributing to the decline of exits and returns. In the early 2020s, venture capital investments, particularly in tech and high-growth startups, experienced unprecedented growth. Fueled by low-interest rates and an expanding economy, venture-backed companies found easier paths to exits through IPOs and acquisitions, often resulting in significant returns for investors. However, by 2023 and continuing into 2024, the landscape had shifted considerably. A combination of economic pressures, increased interest rates, and tighter liquidity saw a steep decline in both the number of exits and the returns generated by VC funds. According to the Q3 2024 PitchBook-NVCA Venture Monitor, the exit environment has been particularly challenging, with exit volumes plummeting to levels unseen in a decade. The report notes that only 14 companies went through a public listing in Q3 2024, and the total exit value for the quarter was just $10.4 billion. This is a stark contrast to the highs seen in previous years, particularly during the pandemic-driven tech boom. Early-stage investments, which typically see longer holding periods and greater uncertainty compared to later-stage or growth-stage investments, have been hit especially hard by this downturn. A significant driver of early-stage investment returns is the ability to secure future funding rounds and eventually exit through an IPO or acquisition. However, the current environment has created bottlenecks at both ends of this spectrum. The Q3 2024 Venture Monitor reports that early-stage deal activity has remained sluggish, with deal counts bottoming out and investors becoming more cautious. Valuations have stayed somewhat elevated, driven by a few large deals in sectors like AI, but this masks the broader trend of a cautious and risk-averse market. Investors are demanding more diligence and protection in term sheets, which has made it harder for early-stage startups to secure the funding they need to grow and eventually exit. At the same time, fundraising for new venture capital funds has been significantly impacted by the lack of distributions. Limited Partners (LPs), who typically reinvest the proceeds from successful exits into new funds, are holding off on committing new capital due to the dearth of returns. The venture ecosystem thrives on the recycling of capital, and with fewer exits generating returns, many early-stage investors are unable to raise new funds at the same pace they did during the boom years. Another significant issue affecting early-stage investments is the slowdown in capital calls. As of 2024, capital calls from VC funds have slowed dramatically, as General Partners (GPs) are wary of asking for new capital without being able to return funds to

GAIIP unveils monumental $100 bn AI data center initiative  

Webscale Tech CapEx vs Chip Vendors’ Data Center Revenues (US$M) (Pic credits: ResearchandMarkets) The “Will The Data Center Gold Rush Come To An End?” report has been added to ResearchAndMarkets‘s offering. This brief is focused on data center demand and the role of generative AI in spurring an uptick in investments, particularly in the webscale sector. Generative AI (GenAI) in all its evolving flavors has captured the attention of the ‘investment community’ – there is a feeling that GenAI is a once in a lifetime opportunity where the early winners have the potential to dominate for decades. This has happened before with other technology breakthroughs and the hype usually dies down. Where is it going now? There is a strong argument that GenAI is a bubble which faces an uphill battle towards widespread adoption. The tools are interesting and do have a range of applications, but they also face serious legal challenges and lack a killer app. There’s also support for the idea that the “smart money” already believes this but doesn’t care, due to confidence in being able to sell others on the hype. Last week a fund was announced to raise and manage up to $100 billion (B) in funding for AI data centers and related energy investments. The new fund, Global AI Infrastructure Investment Partnership (GAIIP), is a partnership between Microsoft and three financial institutions betting big on AI infrastructure: BlackRock, Global Infrastructure Partners (GIP), and Abu Dhabi-based MGX. The new partnership adds to a long list of private equity-driven investments in data centers announced over the last few years. These investments have spiked since late 2022, when ChatGPT was released. Even prior to GenAI rolling out in late 2022/early 2023, new investment vehicles were emerging to raise capital and manage investments in digital infrastructure. With GenAI gaining steam in 2024, that has accelerated. It’s not news that data center spending is surging thanks to widespread enthusiasm for GenAI. The announcements keep on coming: new data centers, bigger and better, consuming more power. New financial vehicles arising to fund all this new infrastructure. With this, a more widespread appreciation of how power-hungry computers actually are – especially the massive clusters of computers prevailing in webscale data centers, now dominated by GPU servers. Energy consumption has doubled in the webscale sector since 2019, growing 15% per year in each of the last two years. More important, since COVID, the webscale sector has become more energy intensive, not less; in 2021, 59 MWh of energy was consumed per US$1M in revenues. That figure grew to 65 in 2022 and 70 in 2023. This is notable, as webscalers are supposed to be able to exploit their size in order to get efficiencies from scale; it’s going the opposite direction with data center power consumption. And energy intensity is likely to keep rising with big commitments to GenAI. Inadequate access to affordable, renewable power is one of many challenges faced by the GenAI market. Despite these challenges, data center spend is

Major Mergers & Acquisitions Signal Exciting Times for Crypto-AI ... - MSN

The Alliance was followed in April by Thoma Bravo’s $5.3bn acquisition of Darktrace, an AI cybersecurity pioneer. In the same week, Cisco purchased Splunk, a platform for searching, monitoring ...

The latest startup news and analysis from Europe

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