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Category: business – Page 48

Colin Murdoch, from Google DeepMind: ‘Gemini will transform the way billions of people live and work’

Google has been dominating the development of artificial intelligence (AI) systems for years. This has undoubtedly been helped by its 2014 acquisition of DeepMind, the London-based startup focused on AI research that developed AlphaGo, a program capable of defeating a grand champion of complex Asian board game Go, which opened debate on whether the AI would eventually surpass the human mind.

But Google’s unquestioned dominance was interrupted last year by another startup — OpenAI. The launch of ChatGPT, the most successful application in history, caught big technology companies off guard, and forced them to accelerate their AI programs. In April of this year, DeepMind — which until then had functioned as a relatively independent research laboratory— and Google Brain — the technology company’s other major research division — merged into a single organization: Google DeepMind, which has some of the best AI scientists in the world.

Colin Murdoch, 45, is the chief business officer of Google’s new AI super division, which has just presented its first toy: Gemini, a multimodal generative AI platform that can process and generate text, code, images, audio and video from different data sources. Those who have used it say that it far surpasses the latest version of ChatGPT, and that it puts Google back in the fight to dominate the market.

OpenAI’s Annualized Revenue Tops $1.6 Billion as Customers Shrug Off CEO Drama

OpenAI recently topped $1.6 billion in annualized revenue on strong growth from its ChatGPT product, up from $1.3 billion as of mid-October, according to two people with knowledge of the figure.

The 20% growth over two months represented in that figure—a measure of the prior month’s revenue multiplied by 12—suggests that the company was able to hold onto its business momentum in selling artificial intelligence to enterprises despite a leadership crisis in November that provided an opening for rivals to go after its customers.

GitHub makes Copilot Chat generally available, letting devs ask questions about code

Earlier this year, GitHub rolled out Copilot Chat, a ChatGPT-like programming-centric chatbot for organizations subscribed to Copilot for Business. Copilot Chat more recently came to individual Copilot customers — those paying $10 per month — in beta. And now, GitHub’s launching Chat in general availability for all users.

As of today, Copilot Chat is available in the sidebar in Microsoft’s IDEs, Visual Studio Code and Visual Studio — included as a part of GitHub Copilot paid tiers and free for verified teachers, students and maintainers of certain open source projects.

“As home to the world’s developers, we’ve brought to market what is now the most widely adopted AI developer tool in history,” Shuyin Zhao, VP of product management at GitHub, told TechCrunch in an email interview. “And code complete was just the beginning.”

Europe’s exascale supercomputer JUPITER to challenge US and China’s dominance

Officially, there are only two exascale supercomputers in the world: Frontier at Oak Ridge National Laboratory in Tennessee and Aurora at Argonne National Laboratory in Illinois. However, it is widely suspected that China has at least two secret exascale machines that have not been tested and ranked by the industry’s 500 list of the most powerful supercomputers in the world.

JUPITER, which stands for Joint Undertaking Pioneer for Innovative and Transformative Exascale Research, will be built at the Jülich Supercomputing Centre in Germany by the European High-Performance Computing Joint Undertaking (EuroHPC JU), a collaboration between the European Union and private businesses.

From graphic design to visual workflows, Canva’s new AI core is changing its business

Canva has crafted a wildly successful business model on the idea that graphic design should be accessible to everyone.

Adams told TechCrunch+ he’s not worried about valuation drops, anyway. “This year has been one of our best years for growth. We’ve almost doubled on most of our metrics. We’ve had 80 million more active users join since this time last year, so it’s just been up and to the right for us,” he said. “That’s what we focus on: more users, better product, revenue growth.”

Over the last 12 months, Canva has released a slew of generative AI products that Adams said gives both the company and its users a new ability to build features and design work that might not have even been considered five years ago. “For us, AI is going to bring human creativity to the next level,” Adams said, noting that AI will enable Canva to “take great visual communication to a billion people around the world.”

Many companies have jumped on the generative AI bandwagon since ChatGPT disrupted the consumer-facing space in November 2022, eliciting eye rolls and suspicion from many a journalist. But with Canva, generative AI hits different. In fact, it’s hard to imagine a better technology to boost Canva’s user growth and revenue generation. Content is the company’s bread-and-butter, the main reason why Canva has been able to scale to such impressive heights and across global boundaries. That’s because the focus has always been on offering images and templates to suit specific geographic audiences.

Giga ML wants to help companies deploy LLMs offline

AI is all the rage — particularly text-generating AI, also known as large language models (think models along the lines of ChatGPT). In one recent survey of ~1,000 enterprise organizations, 67.2% say that they see adopting large language models (LLMs) as a top priority by early 2024.

But barriers stand in the way. According to the same survey, a lack of customization and flexibility, paired with the inability to preserve company knowledge and IP, were — and are — preventing many businesses from deploying LLMs into production.

That got Varun Vummadi and Esha Manideep Dinne thinking: What might a solution to the enterprise LLM adoption challenge look like? In search of one, they founded Giga ML, a startup building a platform that lets companies deploy LLMs on-premise — ostensibly cutting costs and preserving privacy in the process.

Tesla’s Energy & Supercharger Business: A Growing Source of Profit 🔋🔌

Tesla recorded $500M+ in gross profit from its Energy and Services (Supercharging) segments in Q3 2023. Elon Musk noted how strong energy gross margins were on the call, and insinuated strength in these businesses will continue. I think this is a super exciting development for Tesla investors as the company can smooth out cyclicality in it’s automotive business with consistent profits from its Energy and Services.

The Power of Leaders Who Focus on Solving Problems

There’s a new kind of leadership taking hold in organizations. Strikingly, these new leaders don’t like to be called leaders, and none has any expectation that they will attract “followers” personally — by dint of their charisma, status in a hierarchy, or access to resources. Instead, their method is to get others excited about whatever problem they have identified as ripe for a novel solution. Having fallen in love with a problem, they step up to leadership — but only reluctantly and only as necessary to get it solved. Leadership becomes an intermittent activity as people with enthusiasm and expertise step up as needed, and readily step aside when, based on the needs of the project, another team member’s strengths are more central. Rather than being pure generalists, leaders pursue their own deep expertise, while gaining enough familiarity with other knowledge realms to make the necessary connections. They expect to be involved in a series of initiatives with contributors fluidly assembling and disassembling.

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Can you get people excited about the problems that excite you?

Why Quantum Mechanics Defies Physics

The full, weird story of the quantum world is much too large for a single article, but the period from 1905, when Einstein first published his solution to the photoelectric puzzle, to the 1960’s, when a complete, well-tested, rigorous, and insanely complicated quantum theory of the subatomic world finally emerged, is quite the story.

This quantum theory would come to provide, in its own way, its own complete and total revision of our understanding of light. In the quantum picture of the subatomic world, what we call the electromagnetic force is really the product of countless microscopic interactions, the work of indivisible photons, who interact in mysterious ways. As in, literally mysterious. The quantum framework provides no picture as to how subatomic interactions actually proceed. Rather, it merely gives us a mathematical toolset for calculating predictions. And so while we can only answer the question of how photons actually work with a beleaguered shrug, we are at least equipped with some predictive power, which helps assuage the pain of quantum incomprehensibility.

Doing the business of physics – that is, using mathematical models to make predictions to validate against experiment – is rather hard in quantum mechanics. And that’s because of the simple fact that quantum rules are not normal rules, and that in the subatomic realm all bets are off.