Lifeboat Foundation

Businesses must also ensure they are prepared for forthcoming regulations. President Biden signed an executive order to create AI safeguards, the U.K. hosted the world’s first AI Safety Summit, and the EU brought forward their own legislation. Governments across the globe are alive to the risks. C-suite leaders must be too — and that means their generative AI systems must adhere to current and future regulatory requirements.

So how do leaders balance the risks and rewards of generative AI?

Businesses that leverage three principles are poised to succeed: human-first decision-making, robust governance over large language model (LLM) content, and a universal connected AI approach. Making good choices now will allow leaders to future-proof their business and reap the benefits of AI while boosting the bottom line.

A common carbon compound is enabling remarkable performance enhancements when mixed in just the right proportion with copper to make electrical wires. It’s a phenomenon that defies conventional wisdom about how metals conduct electricity.

The findings, reported in the journal Materials & Design, could lead to more efficient electricity distribution to homes and businesses, as well as more efficient motors to power electric vehicles and industrial equipment. The team has applied for a patent for the work, which was supported by the Department of Energy (DOE) Advanced Materials and Manufacturing Technologies Office.

Materials scientist Keerti Kappagantula and her colleagues at DOE’s Pacific Northwest National Laboratory discovered that graphene, single layers of the same graphite found in pencils, can enhance an important property of metals called the temperature coefficient of resistance.

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 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.