Lifeboat Foundation

For example, the New York Times states: “The AI industry this year is set to be defined by one main characteristic: A remarkably rapid improvement of the technology as advancements build upon one another, enabling AI to generate new kinds of media, mimic human reasoning in new ways and seep into the physical world through a new breed of robot.”

Ethan Mollick, writing in his One Useful Thing blog, takes a similar view: “Most likely, AI development is actually going to accelerate for a while yet before it eventually slows down due to technical or economic or legal limits.”

The year ahead in AI will undoubtedly bring dramatic changes. Hopefully, these will include advances that improve our quality of life, such as the discovery of life saving new drugs. Likely, the most optimistic promises will not be realized in 2024, leading to some amount of pullback in market expectations. This is the nature of hype cycles. Hopefully, any such disappointments will not bring about another AI winter.

(Bloomberg) — Google DeepMind, Alphabet Inc.’s research division, said it has taken a “crucial step” towards making artificial intelligence as capable as humans. It involves solving high-school math problems. Most Read from BloombergWall Street Dials Back Fed Wagers After Solid Data: Markets WrapMusk Pressures Tesla’s Board for Another Massive Stock AwardChina’s Economic Growth Disappoints, Fueling Stimulus CallsChina Population Extends Record Drop on Covid Deaths, Low BirthsApple to Allow Outsi.

New advancements in technology frequently necessitate the development of novel materials – and thanks to supercomputers and advanced simulations, researchers can bypass the time-consuming and often inefficient process of trial-and-error.

The Materials Project, an open-access database founded at the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) in 2011, computes the properties of both known and predicted materials. Researchers can focus on promising materials for future technologies – think lighter alloys that improve fuel economy in cars, more efficient solar cells to boost renewable energy, or faster transistors for the next generation of computers.

How can the increased threat of drought and drier conditions from climate change impact groundwater (aquifer) usage, and ultimately, food production? This is what a recent study partially funded by the U.S. Department of Agriculture and published in Nature Water hopes to address as a team of researchers led by the University of Nebraska-Lincoln investigated how decreasing aquifer levels result in irrigation challenges for farmers now only in the United States but throughout the world.

This study holds the potential to help scientists, farmers, and policymakers better understand the appropriate steps to manage irrigation levels as climate change continues to lead to increased drought and drier environmental conditions across the globe.

“In terms of things that let you address food security under extreme conditions — in particular, drought and climate change — we really can’t do without irrigation,” said Dr. Nick Brozović, who is a professor of agricultural economics at the University of Nebraska–Lincoln and a co-author on the study. “If we want to feed the world with high-quality, nutritious food and a stable food supply, we need to irrigate.”

Job replacement has been a key risk factor with advancement in AI-related tech.

The International Monetary Fund (IMF) posits that the potential impact of Artificial Intelligence (AI) on the global job market stands at 40%, with advanced economies anticipated to bear the brunt of this transformation.

In the ever-evolving world of financial markets, understanding the unpredictable nature of stock market fluctuations is crucial. A new study has taken a leap in this field by developing an innovative quantum mechanics model to analyze the stock market.

This model not only encompasses economic uncertainty and investor behavior but also aims to unravel the mysteries behind stock market anomalies like fat tails, volatility clustering, and contrarian effects.

The core of this model is quantum mechanics, a pillar of physics known for explaining the behavior of subatomic particles.

With better food preservation and factories that are more precise along with more upgrades to the global supply line we could even eliminate poverty with the food that is wasted.

It is estimated that 1.3 billion metric tons of food are lost or wasted annually, translating to a financial loss of $1 trillion (USD) per year. And without significant changes, this problem is expected to grow to 2.1 billion metric tons and $1.5 trillion by 2030.

Staggering as these numbers might be, they do not take into account the hidden costs of food production, including labor, storage and salvage or the costs related to customer dissatisfaction, lost opportunities, and inventory/stocking level imprecision.

Continue reading “Food Waste Costs the World’s Economy $1T Each Year” »

The Inevitable Shift towards Machine Labor.
Impact Multiplier of Artificial Cognition and Synthetic Minds.
Economic Benefits of Cognition and Embodied Services.
Addressing Displacement with UBI Funded with Cognitive Services Impact Multipliers.

Navigating the Future with AI, Robotics, and UBI
Introduction.
In the context of the inevitable shift from human labor to machines, particularly in the realm of cognitive and physical tasks, the introduction of advanced technologies like Tesla’s Optimus robot and the development of artificial cognition and synthetic minds carry profound implications.

The Inevitable Shift towards Machine Labor.
The transition from human to machine labor in both cognitive and physical domains is becoming increasingly unavoidable. Technologies like Tesla Optimus represent a significant leap in this direction.

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