Lifeboat Foundation

A subsidy-fueled boom helped build China into an electric-car giant, but with an economic slowdown and hundreds of ride-hailing companies going bust, the country is facing a excess of unwanted batter-powered vehicles. Linda Lew reports on Bloomberg Television.
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Is a non-profit organization that presents a new socio-economic model utilizing science and technology toward social betterment to achieve a sustainable civilization of abundance for all, without exception.

Smaller language models can be based on a billion parameters or less—still pretty large, but much smaller than foundational LLMs like ChatGPT and Bard. They are pre-trained to understand vocabulary and human speech, so the incremental cost to customize them using corporate and industry-specific data is vastly lower. There are several options for these pre-trained LLMs that can be customized internally, including AI21 and Reka, as well as open source LLMs like Alpaca and Vicuna.

Smaller language models aren’t just more cost-efficient, they’re often far more accurate, because instead of training them on all publicly available data—the good and the bad—they are trained and optimized on carefully vetted data that addresses the exact use cases a business cares about.

That doesn’t mean they’re limited to internal corporate data. Smaller language models can incorporate third-party data about the economy, commodities pricing, the weather, or whatever data sets are needed, and combine them with their proprietary data sets. These data sources are widely available from data service providers who ensure the information is current, accurate, and clean.

Google today is rolling out a few new updates to its nearly three-month-old Search Generative Experience (SGE), the company’s AI-powered conversational mode in Search, with a goal of helping users better learn and make sense of the information they discover on the web. The features include tools to see definitions of unfamiliar terms, those that help to improve your understanding and coding information across languages, and an interesting feature that lets you tap into the AI power of SGE while you’re browsing.

The company explains that these improvements aim to help people better understand complicated concepts or complex topics, boost their coding skills and more.

One of the new features will let you hover over certain words to preview their definitions and see related images or diagrams related to the topic, which you can then tap on to learn more. This feature will become available across Google’s AI-generated responses to topics or questions related to certain subjects, like STEM, economics, history and others, where you may encounter terms you don’t understand or concepts you want to dive deeper into for a better understanding.

We need a new philosophical framework for problem solving and global conflict resolutions or we will be finished as a species.

Jeffrey Sachs Interview — Resentment and Nuclear Threats.

Continue reading “Jeffrey Sachs Interview — Resentment and Nuclear Threats” »

AI singularity refers to the future point where artificial intelligence becomes so advanced that it surpasses human intelligence and undergoes rapid, unpredictable self-improvement, leading to an exponential increase in capabilities. At this stage, AI could potentially reshape society, science, and civilization in profound and transformative ways, and its behavior might become difficult for humans to comprehend or control.

The AI alignment problem refers to the challenge of ensuring that artificial intelligence systems are designed and programmed to act in accordance with human values, goals, and intentions. It involves developing AI systems that align with human interests, do not produce harmful outcomes, and operate transparently and predictably, so they can be trusted and reliably controlled. Addressing the AI alignment problem is crucial to avoid potential risks and negative consequences associated with AI development and deployment.

Continue reading “The AI Singularity Future” »

BERLIN, Aug 7 (Reuters) — Taiwanese semiconductor manufacturer TSMC’s (2330.TW) board of directors on Tuesday will decide in favour of building a factory in the German city of Dresden, the Handelsblatt daily reported, citing government sources in Germany.

The German government will provide 5 billion euros ($5.49 billion) to support the construction of the factory, Handelsblatt’s report said on Monday.

The German economy ministry declined to comment on the report, as did the government of the eastern state of Saxony, where Dresden is located.

Elon Musk took over control of the company at a crucial moment.

In the fascinating landscape tech realm, quantum computing stock opportunities could prove to be incredibly lucrative over time. The notion of quantum computing, born over two decades ago, is now gaining solid traction on The Street. Moreover, the technology, rooted in the mysteries of quantum mechanics, aims to boost computing speeds significantly.

The advancements in quantum computing are impossible to ignore, with continuous improvements and decreasing development costs. Moreover, the sector’s convergence with cloud computing opens doors for broader accessibility among researchers and software developers.

Furthermore, as the digital economy and artificial intelligence sectors grow, global spending on cloud computing is expected to reach a whopping $1 trillion annually within the next decade. Quantum computing appears to be on the cusp of becoming a game-changer, and it might be the most opportune time to load up on affordable quantum computing stocks.