Lifeboat Foundation

Lots of experts on AI say it can only be as good as the data it’s trained on — basically, it’s garbage in and garbage out.

So with that old computer science adage in mind, what the heck is happening with Google’s AI-driven Search Generative Experience (SGE)? Not only has it been caught spitting out completely false information, but in another blow to the platform, people have now discovered it’s been generating results that are downright evil.

Continue reading “Google’s Search AI Says Slavery Was Good, Actually” »

Why is everyone so worried about teenagers using AI to write their term papers while no one is talking about AI crashing the financial markets? If high school Pat gets an A they didn’t earn that’s one thing, but Megla Corp using AI to corner the stock market and crash the world economy, well that is quite another. I have no proof that large corporations are in a competition to build the perfect trader, the ultimate hedge fund manager, the killer quant, and the optimal analyst all rolled into one ultra-economist AI, but I know, we all know, in our greedy little capitalist hearts, it’s true. This wanna-be hegemonic corporation will have unleashed an economic weapon that can’t be bargained with, can’t be reasoned with, doesn’t feel pity or remorse or fear, and absolutely will not stop… EVER, until you are broke!

The legendary Hedge fund manager Kyle Reese aside, think about the implications of a trading bot that has even just a 2% advantage and how much money that can mean. Casino empires were built on games that have less advantage than that so you are crazy if you don’t think there is a race to build the ultimate TradeGPT. Everyone is looking for an edge because, in a land where money is king, he or she who owns a money printer owns the crown. Wall Street was an early adopter of computers and networks and they got so far out ahead of the regulators that they crashed the market on Black Monday in 1987 dropping the US market almost 25% in a day that sent reverberations around the world.

Texas A&M University’s board of regents voted to approve the construction of a new institute in Houston that hopes to contribute to maintaining the state’s leadership within the aerospace sector.

This week, the Texas A&M Space Institute got the greenlight for its $200 million plan. The announcement follows a $350 million investment from the Texas Legislature. The institute is planned to be constructed next to NASA’s Johnson Space Center in Houston.

“The Texas A&M Space Institute will make sure the state expands its role as a leader in the new space economy,” John Sharp, chancellor of the Texas A&M System, says in a news release. “No university is better equipped for aeronautics and space projects than Texas A&M.”

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A new study reveals that artificial intelligence models can actually have varying political opinions. Researchers from Washington, Carnegie Mellon, and Xi’an Jiaotong universities worked with 14 large language models (LLMs) and discovered that they all had different political opinions and biases.

According to Interesting Engineering, the researchers presented the language models with 62 politically sensitive statements and asked them to agree or disagree. The answers were then used to create a political compass that measures the degree of social and economic liberalism or conservatism.

Bank of Ireland has apologised for an IT glitch that meant some customers were able to withdraw money they did not have in their accounts at cashpoints.

The bank said it had resolved the “technical issue”, which had also allowed transfers beyond customer limits and had made its online banking and mobile app services unavailable.

Another concern was the dissipation of electrical power on the Enchilada Trap, which could generate significant heat, leading to increased outgassing from surfaces, a higher risk of electrical breakdown and elevated levels of electrical field noise. To address this issue, production specialists designed new microscopic features to reduce the capacitance of certain electrodes.

“Our team is always looking ahead,” said Sandia’s Zach Meinelt, the lead integrator on the project. “We collaborate with scientists and engineers to learn about the kind of technology, features and performance improvements they will need in the coming years. We then design and fabricate traps to meet those requirements and constantly seek ways to further improve.”

Sandia National Laboratories is a multimission laboratory operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration. Sandia Labs has major research and development responsibilities in nuclear deterrence, global security, defense, energy technologies and economic competitiveness, with main facilities in Albuquerque, New Mexico, and Livermore, California.

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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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.