Lifeboat Foundation

After being one of the first plugins to ever come to ChatGPT, Wolfram has now gone all in on the LLM wave. In the latest version 13.3 update, the Wolfram language has added support for LLM technology, as well as integrating an AI model into the Wolfram Cloud.

This update comes on the heels of Wolfram slowly building the tooling for making the language LLM-ready. The update puts LLMs directly into the language with the introduction of an LLM subsystem for the language. It also builds on the LLM functions technology added in May, which ‘packages’ AI powers into a callable function, with the new subsystem now being user-addressable.

With these new updates, developers have a whole new way of interfacing with their data. This approach combines Stephen Wolfram’s idea of natural language programming along with the Wolfram language’s symbolic programming, creating a force to be reckoned with. What’s more, with the Wolfram language API, this can be plugged in to larger systems, delivering amazing power through a natural language interface.

After finding early success with a robot crop-spraying plane, the California startup Pyka has developed an autonomous cargo carrier that could be among the first of a wave of novel electric aircraft to come to market that could change how goods get around.

AI has applications for archeology too! That’s actually a career I considered before computers. I wish I’d gone with that. Long story but computers were kind of a disaster for me.

Nearly a million texts of Akkadian were untranslated before an A.I. was developed that can do it in seconds.

EPFL scientists show that even a few simple examples are enough for a quantum machine-learning model, the “quantum neural networks,” to learn and predict the behavior of quantum systems, bringing us closer to a new era of quantum computing.

Imagine a world where computers can unravel the mysteries of quantum mechanics, enabling us to study the behavior of complex materials or simulate the intricate dynamics of molecules with unprecedented accuracy.

Thanks to a pioneering study led by Professor Zoe Holmes and her team at EPFL, we are now closer to that becoming a reality. Working with researchers at Caltech, the Free University of Berlin, and the Los Alamos National Laboratory, they have found a new way to teach a quantum computer how to understand and predict the behavior of quantum systems. The research has been published in Nature Communications.

As Nvidia’s recent surge in market capitalization clearly demonstrates, the AI industry is in desperate need of new hardware to train large language models (LLMs) and other AI-based algorithms. While server and HPC GPUs may be worthless for gaming, they serve as the foundation for data centers and supercomputers that perform highly parallelized computations necessary for these systems.

When it comes to AI training, Nvidia’s GPUs have been the most desirable to date. In recent weeks, the company briefly achieved an unprecedented $1 trillion market capitalization due to this very reason. However, MosaicML now emphasizes that Nvidia is just one choice in a multifaceted hardware market, suggesting companies investing in AI should not blindly spend a fortune on Team Green’s highly sought-after chips.

The AI startup tested AMD MI250 and Nvidia A100 cards, both of which are one generation behind each company’s current flagship HPC GPUs. They used their own software tools, along with the Meta-backed open-source software PyTorch and AMD’s proprietary software, for testing.

Generative AI’s potential to unleash creativity, accelerate discovery, and enhance efficiency could add trillions to Asian economies.

When it comes to the ability to generate, arrange, and analyze content, generative AI is a gamechanger—one with transformative social and economic potential.

As a technology that is democratized—one that doesn’t simply exist in a faraway lab or tech community in Silicon Valley, for instance—generative AI lowers the barriers to participation. In the age of generative AI, anyone can be a creator. But this also entails a profound workforce shift, changing the processes of production within the economy and, in turn, the types of tasks that are undertaken and the… More.

Meta is taking on Twitter with a new app. Instagram today announced the anticipated launch of its text-based social networking app, Threads, which allows Instagram users to authenticate with their existing credentials in order to post short updates, including text up to 500 characters; links; photos; and videos up to 5 minutes in length.

At launch, Threads is available on iOS and Android in 100 countries, though not in the EU, reportedly due to concerns around adhering to local data privacy regulations. Users can log in with their Instagram credentials, where their username and verification status will carry over. However, Threads profiles can be customized independently as well.

The app’s existence was first scooped by MoneyControl this March and later confirmed by Platformer. In June, Meta previewed the app to employees during a company-wide meeting. Further leaks offered more details about the app’s target market of high-profile celebrities, influencers and artists, and its planned feature set.

Build foundational knowledge of generative AI, including large language models (LLMs), with 4 short videos and get your badge for LinkedIn.

Thousands of ancient cuneiform tablets remain untranslated. A team of researchers have developed an AI to unlock their secrets.