Lifeboat Foundation

There is a joke about the daughter who asks her dad why he speaks so quietly around the house. “Because there is artificial intelligence everywhere that is listening to what we say,” the dad replies. The daughter laughs, the father laughs. And Alexa laughs.

Artificial intelligence does seem to be injecting itself into more and more aspects of our lives. And as AI brains earn the equivalent of a million doctoral degrees while absorbing trillions of bits of data and in turn generate responses with an engaging tone and demeanor that sound as simple and humanlike as your favorite old college professor, some feel compelled to ask: Are computers becoming sentient?

A cynic would respond, “Of course not. Computers may solve problems in seconds that would take humankind generations to solve, but they can’t feel love and pain, can’t see and appreciate the moon and the stars, can’t smell the coffee we spill on the keyboard.”

Researchers from Queen Mary University of London have made a discovery that could change our understanding of the universe. In their study published on August 23 in the journal Science Advances.

<em>Science Advances</em> is a peer-reviewed, open-access scientific journal that is published by the American Association for the Advancement of Science (AAAS). It was launched in 2015 and covers a wide range of topics in the natural sciences, including biology, chemistry, earth and environmental sciences, materials science, and physics.

Apptronik, a robotics company, has unveiled Apollo, a humanoid robot designed to support humans by undertaking hazardous or less desirable tasks, thereby enhancing human safety. Apollo stands out as a leading commercial robot, emphasizing friendly interaction, efficient manufacturing, substantial payload capabilities, and a strong focus on safety.

Researchers have pioneered a 3D-SPI method that allows high-resolution imaging of microscopic objects, presenting a transformative approach for future biomedical research and optical sensing.

A research team led by Prof. Lei Gong from the University of Science and Technology (USTC) of the Chinese Academy of Sciences (CAS) and collaborators developed a three-dimensional single-pixel imaging (3D-SPI) approach based on 3D light-field illumination(3D-LFI), which enables volumetric imaging of microscopic objects with a near-diffraction-limit 3D optical resolution. They further demonstrated its capability of 3D visualization of label-free optical absorption contrast by imaging single algal cells in vivo.

The study titled “Optical Single-Pixel Volumetric Imaging by Three-dimensional Light-Field Illumination” was published recently in the journal Proceedings of the National Academy of Sciences (PNAS).

More than 20 years ago, the human genome was first sequenced. While the first version was full of “holes” representing missing DNA sequences, the genome has been gradually improved in successive rounds. Each has increased the quality of the genome and, in so doing, resolved most of the blank spaces that prevented us from having a complete reading of our genetic material.

The fundamental difficulty researchers faced in reading the genome from end to end is the enormous number of repeated sequences that populate it. The 20,000 or so genes we humans have occupy barely 2% of the entire genome. The remaining 98% is essentially made up of these families of repeated sequences, mobile elements known as transposons and retrotransposons, and—to a lesser but functionally important extent— gene expression regulatory sequences. These function as switches that determine when and where genes are turned on and off.

In March 2022, a major revision of the genome was published in the journal Science. An international consortium of researchers known as “T2T” (telomere to telomere, which are the ends of chromosomes) used a novel strategy based a type of cell (CHM13) that retains only one copy of each chromosome.

Glacial cyclicity of the Earth has often been considered on 100,000 year timescales, particularly for the Late Pleistocene (~11,700 to 129,000 years ago) swapping between periods of extensive polar and mountain glacier ice sheets, to warmer interglacial periods when ice sheets and glaciers retreated, with subsequent sea level rise. This is thought to be related to three key drivers affecting the amount of solar radiation reaching Earth from the sun.

Termed Milankovitch cycles, eccentricity considers the shape of Earth’s orbit changing from circular to more elliptical over 100,000 year timescales, while obliquity refers to the varying ‘tilt’ of the planet’s axis between 22.1 and 24.5 degrees over 41,000 years (contributing to seasons) and precession, which in simple terms is the direction Earth’s axis is pointed and can make the contrast between seasons more extreme in one hemisphere compared to the other.

Continue reading “New research finds Late Pleistocene glaciations terminated by Earth’s axis tilt rather than orbital eccentricity” »

The statement that may not be obvious is that the sleeping giant, Google has woken up, and they are iterating on a pace that will smash GPT-4 total pre-training FLOPS by 5x before the end of the year. The path is clear to 100x by the end of next year given their current infrastructure buildout. Whether Google has the stomach to put these models out publicly without neutering their creativity or their existing business model is a different discussion.

Today we want to discuss Google’s training systems for Gemini, the iteration velocity for Gemini models, Google’s Viperfish (TPUv5) ramp, Google’s competitiveness going forward versus the other frontier labs, and a crowd we are dubbing the GPU-Poor.

Access to compute is a bimodal distribution. There are a handful of firms with 20k+ A/H100 GPUs, and individual researchers can access 100s or 1,000s of GPUs for pet projects. The chief among these are researchers at OpenAI, Google, Anthropic, Inflection, X, and Meta, who will have the highest ratios of compute resources to researchers. A few of the firms above as well as multiple Chinese firms will 100k+ by the end of next year, although we are unsure of the ratio of researchers in China, only the GPU volumes.

To discover how light interacts with molecules, the first step is to follow electron dynamics, which evolve at the attosecond timescale. The dynamics of this first step have been called charge migration (CM). CM plays a fundamental role in chemical reactions and biological functions associated with light–matter interaction. For years, visualizing CM at the natural timescale of electrons has been a formidable challenge in ultrafast science due to the ultrafine spatial (angstrom) and ultrafast temporal (attosecond) resolution required.

Experimentally, the sensitive dependence of CM on molecular orbitals and orientations has made the CM dynamics complex and difficult to trace. There are still some open questions about molecular CM that remain unclear. One of the most fundamental questions: how fast does the charge migrate in molecules? Although molecular CM has been extensively studied theoretically in the last decade by using time-dependent quantum chemistry packages, a real measurement of the CM speed has remained unattainable, due to the extreme challenge.

As reported in Advanced Photonics, a research team from Huazhong University of Science and Technology (HUST), in cooperation with theoretical teams from Kansas State University and University of Connecticut, recently proposed a high harmonic spectroscopy (HHS) method for measuring the CM speed in a carbon-chain molecule, butadiyne (C₄H₂).

Scientists already have their ways of coaxing human cells into new forms, using a special concoction of chemicals to nudge humble skin cells into malleable tissues known as induced pluripotent stem cells.

In spite of this new lease on life, these particular cells still retain a few genetic reminders of their time as a fully developed tissue, affecting their use as a blank slate.

Now an international team of researchers has gone one better: finding a new way of wiping a cell’s memory clean so it can be better reprogrammed as a stem cell.