Serendipity35

It is difficult to keep up with AI advances and new tools. Recently, I have seen the term "superintelligence" being used and I had to look for a definition.

In AI terms, there are three kinds of intelligence. "Artificial Narrow Intelligence" is what we have now. It is "superhuman" at specific tasks like playing Go or translating languages. ChatGPT, Gemini, CoPilot and Meta AI, et al fit in there at the moment.

"Artificial General Intelligence (AGI)" is human-level across the board and can learn anything a person can learn. We’re not quite there yet as of May 2026.

"Artificial Superintelligence (ASI)" is far beyond human level. Philosopher Nick Bostrom popularized the term: and defined it as “any intellect that greatly exceeds the cognitive performance of humans in virtually all domains of interest.”

ASI is what people worry about — or get excited about — when talking about advanced AI. But AGI isn't quite the same as superintelligence. With AGI, you clone the best human brain in software, but with superintelligence that clone keeps upgrading itself until it’s as far beyond us. 

Two new tools are moving closer to the next level.

Google has released TurboQuant, a new compression method that makes AI models cheaper to run and faster to respond. In Google’s reported tests, it reduced the key-value cache, the model’s short-term working memory while it responds, by at least 6x and improved performance by up to 8x on H100 chips, Nvidia’s high-end AI processors used in data centres, while keeping benchmark performance, or standard test performance, close to the original model. That is a serious technical result with a clear business consequence: one of the biggest cost pressures in modern AI may begin to ease. For the past two years, the default logic has been simple. The best AI stayed in the cloud because that is where companies could absorb the cost of running it. TurboQuant starts to weaken that logic.

Meta TRIBE v2 is a foundation AI model that acts like a “digital twin” of the human brain. In plain terms, it’s an AI trained on real brain scan data so it can predict how a person’s brain will respond to things they see, hear, or read. It takes in video, audio, and text, then maps that to about 70,000 areas of the brain to simulate neural activity.  Meta itself says that you can think of it as Meta teaching an AI to “think” more as humans do, by learning directly from brain responses instead of just internet text.

Where did I get information anout Meta's products and path? From their own Muse Spark. That is Meta’s latest (well, as of today) AI assistant model.

Marian Croak, a name that may not be familiar to many, has had a profound impact on the way we communicate today. As a renowned American engineer, Croak has spent her career pushing the boundaries of technology, particularly in the realm of Voice over Internet Protocol (VoIP). With over 200 patents to her name, Croak's work has enabled seamless communication over the internet, revolutionizing the way we connect.

Her  U.S. Patent No. 7,599,359 for VoIP (Voice over Internet Protocol) Technology was ultimately used to create applications such as Zoom, WhatsApp and many others.

Born on May 14, 1955, in New York City, Croak's interest in technology was sparked by her father, who built her a chemistry set that led to her early exploration of the sciences. She pursued her passion for problem-solving at Princeton University, where she earned her undergraduate degree in 1977. Later, she received a PhD in Social Psychology and Quantitative Analysis from the University of Southern California.

Croak's career spans three decades at Bell Labs and AT&T, where she worked on digital messaging applications and VoIP technologies. Her team convinced AT&T to adopt the TCP/IP protocol, which allowed for standardized communication over the Internet. Croak's work on VoIP enabled the conversion of voice data into digital signals, making it possible to transmit voice, text, and video over the internet.

Another of Croak's notable achievements is her patent for text-based donations to charity. Developed in response to Hurricane Katrina, this technology allowed users to donate to organizations using text messaging. The technology was widely used after the 2010 Haiti earthquake, raising over $43 million for relief organizations. Croak received the 2013 Thomas Edison Patent Award for this innovation.

Croak's contributions extend beyond her technical expertise. As a leader at AT&T, she managed over 2,000 engineers and computer scientists, overseeing programs that impacted millions of customers. In 2014, she joined Google as Vice President of Engineering, focusing on expanding internet access and developing Responsible AI.

Throughout her career, Croak has received numerous accolades for her work. She was inducted into the Women in Technology International Hall of Fame in 2016 and the National Inventors Hall of Fame in 2022, becoming one of the first two Black women to receive this honor. She has also been inducted into the National Academy of Engineering and the American Academy of Arts and Sciences.

As Croak herself notes, "Inventors are usually people like you. Sometimes they're good at certain things, other times they're not, and that's ok. Just focus on what you want to change, and you become that change and can make that change happen."

Her legacy serves as a testament to the power of innovation and the impact one person can have on the world. As we continue to navigate the complexities of modern communication, we owe a debt of gratitude to pioneers like Marian Croak, who have worked tirelessly to bring people closer together.

 

In 1981, American physicist and Nobel Laureate Richard Feynman gave a lecture at the Massachusetts Institute of Technology (MIT) in which he outlined a revolutionary idea. Feynman suggested that the strange physics of quantum mechanics could be used to perform calculations. Quantum computing was born. The illustration here shows what one might have imagined it to be back in 1981 - a lind of science-fiction computer.

Quantum computing is a revolutionary area of computing that uses the principles of quantum mechanics to process information in fundamentally different ways than classical computers. In classical computing, information is processed using bits, which are binary and can represent either a 0 or a 1. In quantum computing, however, the fundamental units of information are called qubits. Qubits can exist in a state of 0, 1, or both simultaneously, thanks to a quantum property called superposition. This allows quantum computers to perform multiple calculations at once.

I am not a physicist or computer engineer, so I don't want to go too deeply into that realm. Reading about this, I see the word "entanglement" and have some memory of Einstein referring to quantum entanglement as "spooky action at a distance." He was skeptical since it seemed to defy the principles of classical physics and his theory of relativity. Einstein doubted entanglement, but modern experiments have confirmed its existence and shown that it is a fundamental aspect of quantum mechanics. In quantum computing, entanglement creates strong correlations between qubits, even when they are far apart.

Entanglement enables quantum computers to solve certain types of complex problems much faster than classical computers by leveraging these interconnected qubits. Quantum computers are particularly well-suited to tasks involving massive datasets, optimization problems, simulations, and cryptography. However, they are still in their early stages of development and face challenges such as error rates, stability, and scalability.

In the same way that AI is already in your daily life - even if you don't notice or acknowledge it - quantum computing could be used in everyday activities. It could revolutionize drug discovery and personalized medicine by simulating molecular interactions at an unprecedented speed, leading to faster development of cures and treatments. By solving complex optimization and learning problems, quantum computers could significantly enhance AI's capabilities, leading to smarter assistants and systems.

Cryptography and cybersecurity's current encryption methods could be broken by quantum computers, but they could also enable quantum-safe encryption, making online transactions and communications more secure. There's good and bad in almost every discovery.

In logistics, smarter traffic systems to more efficient delivery routes, quantum computing could optimize logistics, reducing fuel consumption, travel times, and costs.

And quantum computing could impact improved energy solutions, financial modeling, material design, and many things we haven't even considered yet.

Of course, there are challenges. Qubits are highly sensitive to their environment. Even minor disturbances like temperature fluctuations, vibrations, or electromagnetic interference can cause qubits to lose their quantum state—a phenomenon called decoherence. Maintaining stability long enough to perform calculations is a key challenge. Many quantum computers require extremely low temperatures (close to absolute zero) to operate, as qubits need highly controlled environments. Building and maintaining these cryogenic systems is both expensive and challenging.

Small-scale quantum computers exist, but scaling up to thousands or millions of qubits is a monumental task and requires massive infrastructure, advanced error correction mechanisms, and custom hardware, making them cost-prohibitive for widespread adoption.

On the education side of this, quantum computing sits at the intersection of physics, engineering, computer science, and more. A lack of cross-disciplinary expertise will slow down progress in this field.

Google Search has integrated a feature that links directly to the Wayback Machine, allowing users to access archived versions of webpages through search results.

The Wayback Machine is an online archive created by the Internet Archive, a non-profit organization. It allows users to access and view historical snapshots of web pages, dating back to the late 1990s. Essentially, it's like a digital time machine that lets you see how websites looked in the past. This can be useful for research, preserving digital history, or just satisfying curiosity.

By clicking the three dots next to a search result and selecting "More About This Page," users can view how a webpage appeared at different points in time. The collaboration enhances public access to web history, ensuring that digital records remain available for future generations.

Source  https://blog.archive.org/2024/09/11/new-feature-alert-access-archived-webpages-directly-through-google-search/