The first language model was invented over 110+ years ago by Andrey Markov of the Markov Chain fame.
#AI #LLM
Shannon’s said: “OCRO HLI RGWR NMIELWIS”
Jensen Huang, Nvidia’s visionary CEO, challenges a long-held belief about the future of programming. While everyone has been saying it’s crucial to learn coding, Huang turns that idea on its head. With the rise of AI, we are ALL programmers now – without ever writing a line of code.
The real miracle is here: artificial intelligence. It has closed the gap between humans and technology, making complex computing accessible to all. Whether you’re a professional or someone just dipping their toes into the world of tech, AI is now in your hands. Are you going to let this chance slip by? The time to act is now! 🌍🤖
The technology divide is no more. Every government, industry, and business is investing in AI. Will you get on board, or be left in the dust?
Developing large-scale neural network models that mimic the brain’s activity is a major goal in the field of computational neuroscience. Existing models that accurately reproduce aspects of brain activity are notoriously complex, and fine-tuning model parameters often requires significant time, intuition, and expertise.
New published research from an interdisciplinary group of researchers primarily based at Carnegie Mellon University and the University of Pittsburgh presents a novel solution to mitigate some of these challenges. The machine learning-driven framework, Spiking Network Optimization using Population Statistics (SNOPS), can quickly and accurately customize models that reproduce activity to mimic what’s observed in the brain.
Continue reading “Novel framework allows for automated tuning of large-scale neuronal models” »
In a published in the journal npj Computational Materials, Oak Ridge National Laboratory scientists developed a deep learning model—a type of artificial intelligence that mimics human brain function—to analyze high-speed videos of plasma plumes during a process called pulsed laser deposition, or PLD.
Researchers have introduced a solution to the problem of light-sheet fluorescence microscopy: novel illumination beams designed based on deep learning using a trainable phase mask. Their study eliminates the need for sophisticated optical design tools, allowing optimization to be directly applied to improve image contrast.
Why do we study Mars? What missions have been there? How do we plan to explore this intriguing world in the future? Quench your curiosity with this educational infographic on the Red Planet!
For thousands of years, Mars aka the Red Planet, has fascinated skywatchers from countless civilizations and cultures, leading some to speculate that it was a lush world full of life. However, the exploration of Mars has proven to be quite the contrast, instead exhibiting a dry and inhabitable world utterly devoid of life. Despite this, scientists and engineers from around the world have learned quite a bit from our planetary neighbor with the countless robotic explorers sent there, including flybys, orbiters, landers, and rovers.
Through this, we have gained incredible insight into the ancient history of Mars and whether life might have existed there long ago. In the future, as humanity looks to return the first samples from Mars and land humans on the Red Planet’s surface, we will continue to learn more about this fascinating world and whether it could have, or currently, hosts life as we know it.
Continue reading “Mars Exploration: Past, Present, and Future” »
Neuralink rival Synchron is connecting its brain–computer interface with consumer technologies to allow people with paralysis more functionality.
AI can enhance legal efficiency and productivity, but it cannot replace the essential human skills, judgment, and personal involvement required in law practice.
Questions to inspire discussion.
Continue reading “Can Artificial Intelligence Replace Your Lawyer?” »
Researchers at Johannes Gutenberg University Mainz (JGU) have managed to enhance the framework of Brownian reservoir computing by recording and transferring hand gestures to the system which then used skyrmions to detect these individual gestures.
“We were impressed to see that our hardware approach and concept worked so well – and even better than energy-intensive software solutions that employ neural networks,” said Grischa Beneke, a member of Professor Mathias Kläui’s research group at the JGU Institute of Physics.
In collaboration with other experimental and theoretical physicists, Beneke was able to demonstrate that simple hand gestures can be recognized by means of Brownian reservoir computing with a relatively high degree of precision.
It also follows the discovery of a stealthy threat actor that presents itself as a legitimate enterprise and has been advertising automated CAPTCHA-solving services at scale to other cybercriminals and helping them infiltrate IT networks.
Dubbed Greasy Opal by Arkose Labs, the Czech Republic-based “cyber attack enablement business” is believed to have been operational since 2009, offering to customers a toolkit of sorts for credential stuffing, mass fake account creation, browser automation, and social media spam at a price point of $190 and an additional $10 for a monthly subscription.
The product portfolio runs the cybercrime gamut, allowing them to develop a sophisticated business model by packaging several services together. The entity’s revenues for 2023 alone are said to be no less than $1.7 million.
