Lifeboat Foundation

FTX’s fallen CEO, Sam Bankman-Fried, is scheduled to testify tomorrow as a witness before the U.S. House of Representatives Committee on Financial Services.

The committee is investigating the events that led up to FTX’s implosion, which resulted in the crypto exchange filing for bankruptcy last month. Prior to Bankman-Fried testifying, John J. Ray III, the new CEO of FTX, will speak to the House during its first panel.

The hearing, “Investigating the Collapse of FTX, Part I,” sounds like a movie title — and some parts of it probably feel like one, given how crazy this whole situation has become. But questions surrounding what really happened at FTX may remain unanswered; even though Bankman-Fried is scheduled to testify, there are still concerns he may get cold feet.

Microsoft today announced that it acquired Lumenisity, a U.K.-based startup developing “hollow core fiber (HCF)” technologies primarily for data centers and ISPs. Microsoft says that the purchase, the terms of which weren’t disclosed, will “expand [its] ability to further optimize its global cloud infrastructure” and “serve Microsoft’s cloud platform and services customers with strict latency and security requirements.”

HCF cables fundamentally combine optical fiber and coaxial cable. They’ve been around since the ’90s, but what Lumenisity brings to the table is a proprietary design with an air-filled center channel surrounded by a ring of glass tubes. The idea is that light can travel faster through air than glass; in a trial with Comcast in April, a single strand of Lumenisity HCF was reportedly able to deliver traffic rates ranging from 10 Gbps to 400 Gbps.

“HCF can provide benefits across a broad range of industries including healthcare, financial services, manufacturing, retail and government,” Girish Bablani, CVP of Microsoft’s Azure Core business, wrote in a blog post. “For the public sector, HCF could provide enhanced security and intrusion detection for federal and local governments across the globe. In healthcare, because HCF can accommodate the size and volume of large data sets, it could help accelerate medical image retrieval, facilitating providers’ ability to ingest, persist and share medical imaging data in the cloud. And with the rise of the digital economy, HCF could help international financial institutions seeking fast, secure transactions across a broad geographic region.”

The quiet October 29 announcement of the partnership is light on details, stating that Trust Lab and In-Q-Tel — which invests in and collaborates with firms it believes will advance the mission of the CIA — will work on “a long-term project that will help identify harmful content and actors in order to safeguard the internet.” Key terms like “harmful” and “safeguard” are unexplained, but the press release goes on to say that the company will work toward “pinpointing many types of online harmful content, including toxicity and misinformation.”

Though Trust Lab’s stated mission is sympathetic and grounded in reality — online content moderation is genuinely broken — it’s difficult to imagine how aligning the startup with the CIA is compatible with Siegel’s goal of bringing greater transparency and integrity to internet governance. What would it mean, for instance, to incubate counter-misinformation technology for an agency with a vast history of perpetuating misinformation? Placing the company within the CIA’s tech pipeline also raises questions about Trust Lab’s view of who or what might be a “harmful” online, a nebulous concept that will no doubt mean something very different to the U.S. intelligence community than it means elsewhere in the internet-using world.

Thousands of Ukrainian soldiers and civilians are suffering unimaginable injuries in the country’s war with Russia. Many of the more seriously wounded have lost one or more limbs. Now a company in New York is stepping up to help. For access to live and exclusive video from CNBC subscribe to CNBC PRO: https://cnb.cx/2NGeIvi.

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Continue reading “This U.S. company manufactures low-cost, high-quality robotic limbs for Ukraine-Russia war victims” »

Government support is needed, however, to help consumers overcome heat pumps’ higher upfront costs relative to alternatives. The costs of purchasing and installing a heat pump can be up to four times as much as those for a gas boiler. Financial incentives for heat pumps are now available in 30 countries.

In the IEA’s most optimistic scenario – in which all governments achieve their energy and climate pledges in full – heat pumps become the main way of decarbonising space and water heating worldwide. The agency estimates that heat pumps have the potential to reduce global carbon dioxide (CO₂) emissions by at least 500 million tonnes in 2030 – equal to the annual CO₂ emissions of all cars in Europe today. Leading manufacturers report promising signs of momentum and policy support and have announced plans to invest more than US$4 billion in expanding heat pump production and related efforts, mostly in Europe.

Opportunities also exist for heat pumps to provide low-temperature heat in industrial sectors, especially in the paper, food, and chemicals industries. In Europe alone, 15 gigawatts of heat pumps could be installed across 3,000 facilities in these three sectors, which have been hit hard by recent rises in natural gas prices.

‘Pangeos’ is a turtle-shaped ‘terayacht,’ a giant floating city imagined by Italian firm Lazzarini Design Studio. While it only exists as a rendering for now, upon completion it could be the largest floating structure in the world. #yahoofinance.

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Machine learning has increased considerably in several areas due to its performance in recent years. Thanks to modern computers’ computing capacity and graphics cards, deep learning has made it possible to achieve results that sometimes exceed those experts give. However, its use in sensitive areas such as medicine or finance causes confidentiality issues. A formal privacy guarantee called differential privacy (DP) prohibits adversaries with access to machine learning models from obtaining data on specific training points. The most common training approach for differential privacy in image recognition is differential private stochastic gradient descent (DPSGD). However, the deployment of differential privacy is limited by the performance deterioration caused by current DPSGD systems.

The existing methods for differentially private deep learning still need to operate better since that, in the stochastic gradient descent process, these techniques allow all model updates regardless of whether the corresponding objective function values get better. In some model updates, adding noise to the gradients might worsen the objective function values, especially when convergence is imminent. The resulting models get worse as a result of these effects. The optimization target degrades, and the privacy budget is wasted. To address this problem, a research team from Shanghai University in China suggests a simulated annealing-based differentially private stochastic gradient descent (SA-DPSGD) approach that accepts a candidate update with a probability that depends on the quality of the update and the number of iterations.

Concretely, the model update is accepted if it gives a better objective function value. Otherwise, the update is rejected with a certain probability. To prevent settling into a local optimum, the authors suggest using probabilistic rejections rather than deterministic ones and limiting the number of continuous rejections. Therefore, the simulated annealing algorithm is used to select model updates with probability during the stochastic gradient descent process.

@Meet Kevin is a 30-year-old dad and financial analyst. He’s amassed a following of nearly 2 million subscribers on YouTube with his large library of financial content. He recently ran for California governor and owns a lot of Tesla stock.

Meet Kevin’s YouTube: https://www.youtube.com/@MeetKevin.

Continue reading “Meet Kevin Talks Neuralink and Tesla” »

This superintelligent AI is quite astounding learning similarly to a human even. What I am wanting someday is from labor to digital commerce like bitcoin to even stock markets to everything could essentially automated. Also with the neuralink we could essentially have similar intelligence as the superintelligence allowing for humans to attain a superintelligent level of abilities. I think with DNA computers could be better than essentially for implants or essentially downloading information onto human DNA computers or even brain downloads from simple impulses from devices could give binary code files for abilities or making the superintelligence abilities a simple download rather than other forms of technology.

OpenAI has always focused on artificial intelligence (AI) and machine learning advances that benefit humanity. Recently, the company successfully trained a bot to play Minecraft using more than 70,000 hours of gameplay videos. The achievement is far more than just a bot playing a game. It marks a giant stride forward in advanced machine learning using observation and imitation.