Lifeboat Foundation

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.

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.”

Businesses and government agencies must scan code for RSA & old protocols, replacing them with post-quantum cryptography to thwart quantum threats to encryption.

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.

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.”

Continue reading “From graphic design to visual workflows, Canva’s new AI core is changing its business” »

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 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.

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.

Page-utils class= article-utils—vertical hide-for-print data-js-target= page-utils data-id= tag: blogs.harvardbusiness.org, 2007/03/31:999.199848 data-title= The Power of Leaders Who Focus on Solving Problems data-url=/2018/04/the-power-of-leaders-who-focus-on-solving-problems data-topic= Leadership styles data-authors= Deborah Ancona; Hal Gregersen data-content-type= Digital Article data-content-image=/resources/images/article_assets/2018/04/apr18_16_840591218-383x215.jpg data-summary=

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

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.

Continue reading “Why Quantum Mechanics Defies Physics” »