đ€ Q: How quickly will AI and robotics replace human jobs? A: AI and robotics will do half or more of all jobs within the next 3â7 years, with white-collar work being replaced first, followed by blue-collar labor through humanoid robots.
đą Q: What competitive advantage will AI-native companies have? A: Companies that are entirely AI-powered will demolish competitors, similar to how a single manually calculated cell in a spreadsheet makes it unable to compete with entirely computer-based spreadsheets.
đŒ Q: What forces companies to adopt more AI? A: Companies using more AI must outcompete those using less, creating a forcing function for increased AI adoption, as inertia currently keeps humans doing AI-capable tasks.
đ Q: How much of enterprise software development can AI handle autonomously? A: Blitzy, an AI platform using thousands of specialized agents, autonomously handles 80%+ of enterprise software development, increasing engineering velocity 5x when paired with human developers.
Why 2026 Changes Everything for Tesla, Grok & SpaceX
## Elon Muskâs companies, including Tesla and SpaceX, are expected to experience significant breakthroughs and growth in 2026, driven by advancements in AI, robotics, and space technology.
## Questions to inspire discussion.
Tesla Robotaxi & Cybercab Strategy.
đ Q: When will Teslaâs Cybercab production begin and what regulatory hurdle must be cleared first? A: Cybercab production is set to begin on April 1, 2026, but requires federal regulations on autonomous ride-hailing since current rules mandate steering wheels and pedals for non-experimental vehicles.
đ Q: How will Teslaâs robotaxis function as an advertising strategy? A: Robotaxis will serve as Teslaâs primary advertising strategy by acting as an Uber-like service that demonstrates the carsâ capabilities and encourages personal ownership, potentially reducing the need for traditional advertising.
Scodellaro, R., Kulkarni, A., Alves, F. et al. Training convolutional neural networks with the ForwardâForward Algorithm. Sci Rep15, 38,461 (2025). https://doi.org/10.1038/s41598-025-26235-2
MIT researchers have developed a new method for designing 3D structures that can be transformed from a flat configuration into their curved, fully formed shape with only a single pull of a string.
The technique could enable the rapid deployment of a temporary field hospital at the site of a disaster such as a devastating tsunamiâa situation where quick medical action is essential to save lives.
The researchersâ approach converts a user-specified 3D structure into a flat shape composed of interconnected tiles. The algorithm uses a two-step method to find the path with minimal friction for a string that can be tightened to smoothly actuate the structure.
Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive optical networks, in particular, enable large-scale parallel computation through the use of passive structured phase masks and the propagation of light. However, one major challenge remains: systems trained in model-based simulations often fail to perform optimally in real experimental settings, where misalignments, noise, and model inaccuracies are difficult to capture.
In a new paper published in Light: Science & Applications, researchers at the University of California, Los Angeles (UCLA) introduce a model-free in situ training framework for diffractive optical processors, driven by proximal policy optimization (PPO), a reinforcement learning algorithm known for stability and sample efficiency. Rather than rely on a digital twin or the knowledge of an approximate physical model, the system learns directly from real optical measurements, optimizing its diffractive features on the hardware itself.
âInstead of trying to simulate complex optical behavior perfectly, we allow the device to learn from experience or experiments,â said Aydogan Ozcan, Chancellorâs Professor of Electrical and Computer Engineering at UCLA and the corresponding author of the study. âPPO makes this in situ process fast, stable, and scalable to realistic experimental conditions.â
One of the worldâs foremost philosophers of physics, Maudlin is Professor of Philosophy at NYU and Founder and Director of the John Bell Institute for the Foundations of Physics.
Why do imaginary numbers appear at the foundation of quantum mechanics? This question, which puzzled even great physicists like Eugene Wigner, opens up deeper issues about what it means to explain features of the mathematical formalism used in physical theory. Join philosopher of science Tim Maudlin as he explores that question through the lens of quantum dynamics, arguing that the appearance of complex numbers in Schrödingerâs equation is not arbitrary, but motivated by the need for a particular kind of wave-like structure in fundamental dynamics.
The Pooled Cohort Equations (PCE) cardiovascular risk score stratifies risk for multiple ocular diseases, according to a study published online in Ophthalmology.
Deyu Sun, Ph.D., from the David Geffen School of Medicine at the University of California Los Angeles, and colleagues conducted a historical prospective cohort study using electronic health record data from the âAll of Usâ Research Program to examine whether the PCE cardiovascular risk score is associated with future age-related macular degeneration (AMD), glaucoma, diabetic retinopathy (DR), retinal vein occlusion (RVO), and hypertensive retinopathy (HTR).
A total of 35,909 adults aged 40 to 79 years with complete variables for PCE calculation within a six-month period were included in the study. Individual-level PCE score was classified into four risk categories.
AI is everywhere, yet many feel anxious using it. This resistance stems from psychology, not just technology. Because algorithms operate as âblack boxesâ we cannot interrogate, we feel disempowered and instinctively distrust decisions we cannot understand.
Jim talks with Ben Goertzel about the ideas in his recent essay âThree Viable Paths to True AGI.â They discuss the meaning of artificial general intelligence, Steve Wozniakâs basic AGI test, whether common tasks actually require AGI, a conversation with Joscha Bach, why deep neural nets are unsuited for human-level AGI, the challenge of extrapolating world-models, why imaginative improvisation might not be interesting to corporations, the 3 approaches that might have merit (cognition-level, brain-level, and chemistry-level), the OpenCog system Ben is working on, whether itâs a case of âgood old-fashioned AI,â where evolution fits into the approach, why deep neural nets arenât brain simulations & attempts to make them more realistic, a hypothesis about how to improve generalization, neural nets for music & the psychological landscape of AGI research, algorithmic chemistry & the origins of life problem, why AGI deserves more resources than itâs getting, why we may need better parallel architectures, how & how much society should invest in new approaches, the possibility of a cultural shift toward AGI viability, and much more.
Einstein never liked the idea that nature is uncertain and he once said âdoes that mean the Moon is not there when I am not looking at itâ. He believed we live in an orderly Universe which is fundamentally rational and that there should always be a reason why thing happen. But there is a way to have the objective Universe of Einstein and the uncertainty of quantum physics and that is by explaining quantum mechanics as the physics of âtimeâ with the future as an emergent property.
In this radical theory the mathematics of quantum mechanics represents the physics of âtimeâ as a physical process with classical physics representing process over a period of time as in Newtonâs differential equations. This is a process formed by the spontaneous absorption and emission of light photon energy. This forms a continuous process of energy exchange that forms the ever changing world of our everyday life.
The Universe is a continuum with the future coming into existence photon by photon with each new photon electron coupling or dipole moment. This forms the movement of positive and negative charge with the continuous flow of electromagnetic fields.
Consciousness in the form of electrical activity in the brain is the most advanced part of this process and can therefore comprehend this process as âtimeâ. With a past that has gone forever and a future that is always uncertain in the form of a probability function or quantum wave particle function that is explained mathematically by Schrödingerâs wave equation Κ. Therefore each individual is in the centre of their own reference frame as an interactive part of this process. With their own time line from the past into the future being able to look back in time in all directions at the beauty of the stars! It is this personalization of the brain being in âthe moment of nowâ in the center of its own reference frame that gives us the concept of âmindâ with each one of us having our own personal view of the beauty and uncertainty of life.
It is not that there is uncertainty if the Moon is there or not if nobody looks. It is that the physical act of looking will form new light photon oscillations or vibrations relative to the actions of the observer in a continuous flow of cause and effect. The wave particle duality of light is acting like the bits or zeros and ones of a computer. This forms an interactive process continuously forming a blank canvas that we can interact with turning the possible into the actual! Any observation of the Moon will be over a period of time with the wave nature of light explaining diffraction, interference, reflection and refraction. But the particle nature of light the âphotonâ will only come into existence when the light comes in contact with the lenses and mirrors of the telescope being used. And finally with new photons be formed in the eye of the observer the uncertainty of the observation will be completed using both the wave and particle nature of light!
What we see in our everyday life as an uncertain future is formed by a physical process that at the smallest scale is represented mathematically by Heisenbergâs Uncertainty Principle âĂâpĂâ„h/4Ï with the Planck constant ħ=h/2Ï being a constant of action in the dynamics geometry of space and time! This theory takes quantum potential, electrical potential and gravitational potential and combines them into one universal process. That explains why we all have a potential future in our everyday life that is always uncertain. This is done by making the future an emergent property energy âE slows the rate that time ât flows creating a future relative to the energy and momentum of each object or life form. For in this theory creation is truly in the hand and eye of the beholder with an objective reality in the form of a dynamic interactive process that forms an infinity of possibilities. Please share and subscribe it will help the promotion of this theory!
