Review all news, announcements and videos from the 2024 IBM Think Event.
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Fast radio bursts (FRBs) are one of the greater mysteries facing astronomers today, rivaled only by gravitational waves (GWs) and gamma-ray bursts (GRBs). Originally discovered in 2007 by American astronomer Duncan Lorimer (for whom the “Lorimer Burst” is named), these short, intense blasts of radio energy produce more power in a millisecond than the sun generates in a month.
In most cases, FRBs are one-off events that brightly flash and are never heard from again. But in some cases, astronomers have detected FRBs that were repeating in nature, raising more questions about what causes them.
Prior to the discovery of FRBs, the most powerful bursts observed in the Milky Way were produced by neutron stars, which are visible from up to 100,000 light-years away. However, according to new research led by the Netherlands Institute for Radio Astronomy (ASTRON), a newly detected FRB was a billion times more radiant than anything produced by a neutron star.
The world’s most active volcano is at it again after Hawaii’s Kilauea began its seventh episode of its ongoing eruption, with video showing lava shooting more than 100 feet into the air.
The OS axiom posits that reality operates like a computational construct. Think of it as an evolving cosmic master algorithm—a fractal code that is both our origin and our ultimate destiny. This axiom doesn’t diminish the beauty or mystery of existence; on the contrary, it elevates it. When we think of the universe as a computation, we realize that the laws of physics, the flow of time, and even the emergence of consciousness are not random accidents but inevitable outcomes of this higher-order system.
This concept naturally leads us to the Omega Singularity, a term I use to describe the ultimate point of universal complexity and consciousness. Inspired by Pierre Teilhard de Chardin’s Omega Point, this cosmological singularity is where all timelines of evolution, computation, and consciousness converge into a state of absolute unity—a state where the boundaries between the observer and the observed dissolve entirely. In The Omega Singularity, I elaborate on how this transcendent endpoint represents not just the culmination of physical reality but the quintessence of the “Universal Mind” capable of creating infinite simulations, much like we create virtual worlds today.
But let’s take a step back. How does this all relate to the OS axiom? If the universe is computational, it means that all processes—be they physical, biological, or cognitive—are governed by fundamental rules, much like a computer program. From the fractal geometry of snowflakes to the self-organizing principles of life and intelligence, we see the OS postulate at work everywhere. The question then becomes: Who or what wrote the code? Here, we enter the realm of metaphysics and theology, as explored in Theogenesis and The Syntellect Hypothesis. Could it be that we, as conscious agents, are co-authors of this universal script, operating within the nested layers of the Omega-God itself?
It is widely recognized that continuously scaling both data size and model size can lead to significant improvements in model intelligence. However, the research and industry community has limited experience in effectively scaling extremely large models, whether they are dense or Mixture-of-Expert (MoE) models. Many critical details regarding this scaling process were only disclosed with the recent release of DeepSeek V3. Concurrently, we are developing, a large-scale MoE model that has been pretrained on over 20 trillion tokens and further post-trained with curated Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF) methodologies. Today, we are excited to share the performance results of and announce the availability of its API through Alibaba Cloud. We also invite you to explore on Qwen Chat!
We evaluate alongside leading models, whether proprietary or open-weight, across a range of benchmarks that are of significant interest to the community. These include MMLU-Pro, which tests knowledge through college-level problems, LiveCodeBench, which assesses coding capabilities, LiveBench, which comprehensively tests the general capabilities, and Arena-Hard, which approximates human preferences. Our findings include the performance scores for both base models and instruct models.
An AI model created to design proteins simulates 500 million years of protein evolution in developing a previously unknown bright fluorescent protein.
Learn more in a new Science study.
More than three billion years of evolution have produced an image of biology encoded into the space of natural proteins. Here we show that language models trained at scale on evolutionary data can generate functional proteins that are far away from known proteins. We present ESM3, a frontier multimodal generative language model that reasons over the sequence, structure, and function of proteins. ESM3 can follow complex prompts combining its modalities and is highly responsive to alignment to improve its fidelity. We have prompted ESM3 to generate fluorescent proteins. Among the generations that we synthesized, we found a bright fluorescent protein at a far distance (58% sequence identity) from known fluorescent proteins, which we estimate is equivalent to simulating five hundred million years of evolution.
A study led by researchers from the University of Virginia has used satellite measurements to show the long-term persistence of air pollution inequalities tied to industrialized swine facilities in Eastern North Carolina.
Using satellite data spanning a 15-year period from 2008–2023, the study quantifies disparities in ammonia (NH3)—an air pollutant emitted by swine operations—for Black, Hispanic and Indigenous communities. These inequalities, exacerbated by hot and calm weather conditions, extend for multiple kilometers beyond the immediate vicinity of the facilities, highlighting the widespread impact of this environmental issue.
The study, published in Environmental Science & Technology by Sally Pusede and her team in the Department of Environmental Sciences at UVA, uses data from the Infrared Atmospheric Sounding Interferometer (IASI) aboard multiple polar-orbiting satellites. By analyzing NH3 levels in the atmosphere, UVA researchers were able to show that emissions from industrial swine operations result in systematic environmental inequalities.
In a study published in Cell, a research team led by Zhu Shujia from the Center for Excellence in Brain Science and Intelligence Technology of the Chinese Academy of Sciences (CAS), along with Li Yang from the Shanghai Institute of Materia Medica of CAS, has dissected the assembly and architecture of endogenous N-methyl-ᴅ-aspartate receptors (eNMDARs) in the adult mammalian cerebral cortex and hippocampus.
Learning and memory are fundamental brain functions that underlie human cognition and perception of the world, which rely on development-and activity-dependent synaptic plasticity. NMDA receptors, members of the excitatory ionotropic glutamate receptor family, are essential to these processes.
They regulate the strength of synaptic connections, playing a critical role in advanced brain functions. In higher brain structures involved in cognition, such as the cerebral cortex and hippocampus, they are especially vital for cognitive function.
