Lifeboat Foundation

Targeted drugs aim to pinpoint the exact location in the body where diseased tissue is located and where the medicine is required. The manifold benefits of administering a targeted drug include heightened efficacy, as the drug is meticulously designed for specificity, thereby reducing side effects, and minimizing damage to healthy tissue. Consequently, this approach enhances the patient’s quality of life during treatment.

Oligonucleotides (ONs), specifically designed short chains of DNA or RNA, have emerged as a crucial tool with immense potential in personalized medicine. These therapeutic ONs are already in use for conditions, such as certain types of muscular dystrophy and liver disease, which conventional drugs cannot address.

Depending on the type, ONs can function by, preventing or changing the production of a protein in the cell, particularly beneficial in diseases caused by the overproduction of a specific protein.

“The human brain has 100 billion neurons, each neuron connected to 10,000 other neurons. Sitting on your shoulders is the most complicated object in the known universe.” — Michio Kaku, PhD.

Since most examples of brain-inspired silicon chips are based on digital electronic principles, their capacity to fully imitate brain function is limited. Self-organizing brain organoids connected to microelectrode arrays (MEAs) can be changed in function to create neural networks. These networks, called organoid neural networks (ONNs), show the capacity for unsupervised learning, which is what artificial intelligence (AI) is based on. These mini-organs, when connected to the right hardware, can even be trained to recognize speech.

This brain-inspired computing hardware, or “Brainoware,” could overcome existing shortcomings in AI technologies, providing natural solutions to challenges regarding time and energy consumption and heat production of current AI hardware. These ONNs may also have the necessary complexity and diversity to mimic a human brain, which could inspire the development of more sophisticated and human-like AI systems.

I think it’s got potential to be a magnificent vehicle.

Tesla CEO Elon Musk is planning on opening his own STEM-focused primary and secondary school, and eventual an university in Austin, Texas, according to tax filings.

Future quantum computers are expected to revolutionize problem-solving in various fields, such as creating sustainable materials, developing new medications, and unraveling complex issues in fundamental physics. However, these pioneering quantum systems are currently more error-prone than the classical computers we use today. Wouldn’t it be nice if researchers could just take out a special quantum eraser and get rid of the mistakes?

Reporting in the journal Nature, a group of researchers led by Caltech is among the first to demonstrate a type of quantum eraser. The physicists show that they can pinpoint and correct for mistakes in quantum computing systems known as “erasure” errors.

“It’s normally very hard to detect errors in quantum computers, because just the act of looking for errors causes more to occur,” says Adam Shaw, co-lead author of the new study and a graduate student in the laboratory of Manuel Endres, a professor of physics at Caltech. “But we show that with some careful control, we can precisely locate and erase certain errors without consequence, which is where the name erasure comes from.”

Artificial Intelligence (AI) is changing.

AI is changing and it will continue to do so — although this year of generative AI stands out as a seminal moment in time — now we need the right developer tools.

Bad things can happen when you hallucinate. If you are human, you can end up doing things like putting your underwear in the oven. If you happen to be a chatbot or some other type of artificial intelligence (AI) tool, you can spew out false and misleading information, which—depending on the info—could affect many, many people in a bad-for-your-health-and-well-being type of way. And this latter type of hallucinating has become increasingly common in 2023 with the continuing proliferation of AI. That’s why Dictionary.com has an AI-specific definition of “hallucinate” and has named the word as its 2023 Word of the Year.

Dictionary.com noticed a 46% jump in dictionary lookups for the word “hallucinate” from 2022 to 2023 with a comparable increase in searches for “hallucination” as well. Meanwhile, there was a 62% jump in searches for AI-related words like “chatbot”, “GPT”, “generative AI”, and “LLM.” So the increases in searches for “hallucinate” is likely due more to the following AI-specific definition of the word from Dictionary.com rather than the traditional human definition:

hallucinate [ h uh-loo-s uh-neyt ]-verb-(of artificial i ntelligence) to produce false information contrary to the intent of the user and present it as if true and factual. Example: When chatbots hallucinate, the result is often not just inaccurate but completely fabricated.

Continue reading “Dictionary.com 2023 Word Of The Year ‘Hallucinate’ Is An AI Health Issue” »

It features a sleek aerodynamic design, no tilt mechanisms or extra parts, eliminating failures and unnecessary weight for efficient vertical flight.

The innovative aerial solution is ideal for high-precision mapping to agriculture, ensuring efficient coverage in every flight.

Continue reading “Aeromao introduces the world’s first water-landing fixed-wing drone” »

NASA has awarded GE Aerospace a contract to continue working on the HyTEC program, which aims to create more fuel-efficient and eco-friendly engines for commercial aircraft.

NASA has renewed a contract with GE Aerospace to continue the HyTEC program, which aims to create more fuel-efficient engines for commercial aircraft.

Continue reading “GE Aerospace advances sustainable engine tech with NASA contract” »