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Swiss tech firm launches AI made of human brain cells rental service

The organoids only live about 100 days, then, ostensibly, the AI dies.

Swiss technology firm FinalSpark recently launched a program that allows scientists to rent cloud access to “biocomputers” made out of human brain cells for a mere $500 a month. 

The purpose of these biocomputers, according to FinalSpark, is to develop a highly efficient, low-energy solution to the ballooning costs associated with developing artificial intelligence models. The company says it could be as much as 100,000 times more efficient to use computers made of organic material to train AI than it is to use traditional silicon-based technology.

According to FinalSpark founder Fred Jordan, Neurospark is the only company to offer access to computers made out of clumps of human brian cells (called organoids). Their technology can be viewed live online.

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AI researchers want to solve the bot problem by requiring ID to use the internet

The researchers based their ideas on “proof of personhood” technologies developed by the blockchain community.

Artificial intelligence researchers are worried that AI bots are eventually going to take over the internet and spread like a digital invasive species. Rather than approach the problem by attempting to limit the proliferation of bots and AI-generated content, one team decided to go in the opposite direction. 

In a recently published preprint paper, dozens of researchers advocate for a system by which humans would need to have their humanity verified in-person by another human in order to obtain “personhood credentials”

The big idea appears to be the creation of a system wherein someone could prove they were human without having to disclose their identity or any further information. If that sounds familiar to those of you in the crypto community, it’s because the research is based on “proof of personhood” blockchain technologies.

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Quantum computers are advancing much faster than scientists expected

Breakthroughs in scalability, error-correction, and infrastructure have led to an accelerated timeline for quantum advantage.

Quantum computing is one of those “just around the corner” technologies that has the scientific community split. Tech outfits such as Google and IBM have gone full throttle with both R&D and marketing as if they’re already here while many independent researchers have claimed quantum computers will never work. 

Most people working in the field, however, believe that quantum computers will be able to solve problems that classical computers can’t within the next 10 years.

This is according to a recent survey of 927 people with associations to the field of quantum computing (researchers, executives, press, enthusiasts, etc.) conducted by QuEra. Of those surveyed, 74.9% “expect quantum to be a superior alternative to classical computing for certain workloads” within the next 10 years.

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German quantum breakthrough highlights need for particle physicists in crypto

German quantum breakthrough highlights need for particle physicists in crypto

Breakthrough quantum computing research out of Germany could lead to a revolution in particle physics with implications for finance, economics, and cryptocurrency. It might be time for firms in the crypto industry to add chief science officers and particle physicists to their portfolios. 

Much like the tech industry before it, crypto has bootstrapped itself on the virtue of its own feats of engineering and innovation. The engineering and innovation it took to invent blockchain and cryptocurrency are, arguably, analogous to the advent of personal computing and the internet.

Over the past 20 years, however, the tech industry has shifted towards hard science. Perhaps it’s time for crypto to follow suit.

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Ripple publishes math prof’s warning: ‘public-key cryptosystems should be replaced’

Mathematician Massimiliano Sala says current encryption methods won’t protect blockchain systems from quantum computers.

Professor Massimiliano Sala, of the University of Trento in Italy, recently discussed the future of blockchain technology, as it relates to encryption and quantum computing, with the crew at Ripple as part of the company’s ongoing university lecture series. 

Sala’s discussion focused on the potential threat posed by quantum computers as the technology matures. According to the professor, current encryption methods could be easy for tomorrow’s quantum computers to solve, thus putting entire blockchains at risk.

Per Sala:

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Harvard built hacker-proof quantum network in Boston using existing fiber cable

According to the scientists, the 22-mile distance between nodes is the longest quantum fiber network to date.

Physicists at Harvard University have built what they believe is the world’s longest secure quantum communications network using 22 miles of currently existing fiber-optic cables.

The experiment, published in the scientific journal Nature, connected two functional quantum computer nodes to each other through a strange physical phenomenon called “entanglement.” This allowed them to share data across the 22-mile distance in a paradigm that, according to the laws of physics, is unhackable.

The world is currently embroiled in a technological race to shore up global computer security ahead of “Q Day,” a hypothetical point in the near future when bad actors will have access to quantum computers powerful enough to shred current encryption methods.

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Harvard scientists claim breakthrough, ‘advent of early error-corrected quantum computation’

The team’s results, once reviewed, could represent a significant milestone in quantum computing research.

When industry insiders talk about a future where quantum computers are capable of solving problems that classical, binary computers can’t, they’re referring to something called “quantum advantage.”

In order to achieve this advantage, quantum computers need to be stable enough to scale in size and capability. By-and-large, quantum computing experts believe the largest impediment to scalability in quantum computing systems is noise.

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Changpeng Zhao’s next move could involve decentralized science

Decentralized science, or DeSci, aims to apply decentralized business models to medical research.

Changpeng “CZ” Zhao’s tenure as the CEO of Binance may be over, but the exchange giant’s loss could be a boon for the decentralized science (DeSci) sector.

In a comment on X (formerly Twitter) on Tuesday, Nov. 28, the former Binance CEO revealed an interest in the rapidly developing sector.

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Researchers in China developed a hallucination correction engine for AI models

The “Woodpecker” hallucination correction system can, ostensibly, be applied to any multi-modal large language model, according to the research.

A team of scientists from the University of Science and Technology of China and Tencent’s YouTu Lab have developed a tool to combat “hallucination” by artificial intelligence (AI) models. 

Hallucination is the tendency for an AI model to generate outputs with a high level of confidence that don’t appear based on information present in its training data. This problem permeates large language model (LLM) research. Its effects can be seen in models such as OpenAI’s ChatGPT and Anthropic’s Claude.

The USTC/Tencent team developed a tool called “Woodpecker” that they claim is capable of correcting hallucinations in multi-modal large language models (MLLMs).

This subset of AI involves models such as GPT-4 (especially its visual variant, GPT-4V) and other systems that roll vision and/or other processing into the generative AI modality alongside text-based language modelling.

According to the team’s pre-print research paper, Woodpecker uses three separate AI models, apart from the MLLM being corrected for hallucinations, to perform hallucination correction.

These include GPT-3.5 turbo, Grounding DINO, and BLIP-2-FlanT5. Together, these models work as evaluators to identify hallucinations and instruct the model being corrected to re-generate its output in accordance with its data.

In each of the above examples, an LLM hallucinates an incorrect answer (green background) to prompting (blue background). The corrected “Woodpecker” responses are shown with a red background. (Image source: Yin, et. al., 2023).

To correct hallucinations, the AI models powering “Woodpecker” use a five-stage process that involves “key concept extraction, question formulation, visual knowledge validation, visual claim generation, and hallucination correction.”

The researchers claim these techniques provide additional transparency and “a 30.66%/24.33% improvement in accuracy over the baseline MiniGPT-4/mPLUG-Owl.” They evaluated numerous “off the shelf” MLLMs using their method and concluded that Woodpecker could be “easily integrated into other MLLMs.”

Related: Humans and AI often prefer sycophantic chatbot answers to the truth — Study

An evaluation version of Woodpecker is available on Gradio Live where anyone curious can check out the tool in action.

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DAOs can help scientists find funding and community, says Nature science journal

Decentralization could help bring scientists in underfunded fields and locations to the table without requiring relocation or reemployment

The Nature science journal recently published an editorial in its Nature Bioscience section lauding the use of decentralized autonomous organizations (DAOs) as a revolutionary new method by which researchers working in underfunded scientific fields can create communities around their work and raise funding which, otherwise, might not be available.

In a DAO-based research scheme, a project’s organization, fundraising, feedback, and pipeline from discovery to product/industry can all be handled by the same decentralized governing body.

Per the Nature article, the general workflow would also be streamlined compared to the status quo:

“Project proposals are sent to the DAO, and each DAO member is able to vote on whether a particular project should be funded. Members have tokens … to provide support and feedback to new project proposals. Research results are also provided to the DAO as projects continue, leading to further feedback and engagement. Eventually, the project will (hopefully) end up in an IP-NFT (intellectual property non-fungible token) — something like a patent, which is owned by the DAO and governed by all token holders.”

Funding can vary wildly from one scientific endeavor to another. During boom and bust periods, research into areas such as AI and quantum computing might receive huge boons from big tech, government, and follow-on investors while sectors which may have been well-funded previously, such as longevity, or those that have been traditionally underfunded, women’s health issues for example, may find funding increasingly difficult to secure.

DAOs are built on blockchain technology. This allows them to function on a digital ledger that is transparent and decentralized – meaning it isn't controlled by a single entity or institution. In the science world, this means that project funding and community interaction can be democratized.

Related: DAOs need to learn from Burning Man for mainstream adoption

Traditionally, those scientists working at or with the most prestigious institutions — major universities in countries with high GDPs, government institutions and contractors, big tech and big pharma companies — not only receive the most funding, but also have access to the most potential funding.

The distinction is important because, as scientists leave geographical areas with less funding to pursue research in wealthier areas, the “brain drain” associated with emigration is compounded.

And, because DAOs don’t necessarily have to respect borders (though the legalities surrounding their operation can vary by location), they can be governed by the needs and wishes of the scientists performing the research, not the country, university, or company sponsoring it.

Ultimately, the Nature editorial staff concludes that DAOs could become a crucial platform for underfunded researchers, but adoption will require further education.

“Part of this challenge is helping possible members realize that the DAO is not just a funding body,” the staff writes, “but also a community of people who care strongly about supporting a particular scientific cause.”

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