Global AI Show’s Post

MiBMI: new neural chip 91% accurate!✨ The new neural chip from the EPFL labs in Switzerland impresses with its small size, low power consumption and high accuracy in converting neural activity 🧠 into text.🔠 How? The chip is able to identify the specific neural markers of each letter without having to process additional brain stimuli, thus saving time and energy.  The applications of this technology will improve people’s life, for example by giving a voice to those who today have no way of expressing themselves, but it will also allow new frontiers of human-machine interaction to be explored.🔮 To know more, check this article: https://lnkd.in/dNnhzc_E Stay tuned to know when our product will be released! Start following us on Superhum.ai 🚀 #ai #tech #neuralchip #brain #text #medicine #innovation #betterlifebetterfuture #joinus #superhum.ai

AI made from brain cells in a petri dish can recognise your voice 🧠 Welcome to the future. Well not yet, but in some proof-of-concept work out of Indiana University Bloomington, a research team under Feng Guo incubated brain organoids — clumps of living nerve cells — and then trained them to distinguish one person’s voice. After two days of training, the cells were up to 80% accuracy. Not bad for a clump of cells. Part of the hope from this research is actually to find more energy efficient substrates for AI — silicon transistors use a lot of energy. Unfortunately, these tiny biocomputers don’t last very long out there in the world without a body to keep them alive. But the biocomputing field that this research falls into may make some seriously important contributions to the AI field in the future if it means we can fit powerful AI into the dense material of neurons. #ai #artificialintelligence #biocomputing #brains #airesearch ——— For more news, tips and thoughtful discussion on AI in academia, sign up to our free weekly newsletter: The AI Academic. Link in profile. Dr. Fox, The AI Academic 🦊

Hong Kong scientists are on a quest to revolutionize artificial intelligence by drawing inspiration from the most complex system known - the human brain. Led by Li Can at the University of Hong Kong, the team is exploring the potential of memristors, devices that emulate the brain's synapses and neurons, to create AI that can learn and function throughout a lifetime. This innovative approach could lead to AI that operates with the efficiency and adaptability of the human mind, surpassing current computing limitations. With a recent funding boost from the Croucher Tak Wah Mak Innovation Awards, the team is poised to advance their research, which could have far-reaching implications, from enhancing mobile devices to accelerating genome sequencing. Could this brain-inspired technology be the key to the next AI breakthrough? And what ethical considerations should we address as AI begins to mirror human cognitive processes? Let me know what you think! #hongkong #artificialintelliegence #humanbrain #aitechnology

*A Bridge between Academia and Industries: Seminars at Politecnico di Milano* Today, I had the honor of participating in a seminar at Politecnico di Milano, where I had the opportunity to share with bioengineering students the innovations and milestones of Canon Medical in the field of artificial intelligence applied to imaging technologies. Together, we explored how AI is revolutionizing diagnostic imaging, with a significant impact not only on image quality but also on the entire examination and processing workflows. The seminar was also a valuable opportunity to exchange ideas, with students asking inspiring questions, with curiosity and innovative spirit. This underscored the importance of collaboration between university and industry to address the healthcare challenges. #canonmedical #AiCE #madeforlife #AI #deeplearning #bioengineering

🚀💡 Breaking News for Tech Enthusiasts! 💡🚀 Imagine a world where human brain cells are not just the stuff of consciousness, but also key players in cutting-edge technology. That's right, scientists have just achieved something remarkable: connecting human brain cells to a computer chip to perform speech recognition tasks! This could be a game-changer in the field of brain-computer interfaces, paving the path to innovations we've only seen in sci-fi movies. The study involved brain cells grown in the lab, forming mini-brains called "brain organoids". These were then interfaced with a chip that converted the organoid's neural activity into a recognizable output. And guess what? It successfully identified spoken sentences with impressive accuracy. What does this mean for the future of #TechInnovation and #AI? Could we be on the verge of developing machines that don't just mimic human-like processing but actually incorporate biological elements? Think of the possibilities: enhanced speech recognition systems, revolutionary neuroprosthetics, or even new ways to treat brain disorders. But it's not just about what this technology can do; it's a conversation starter on the ethical implications and the future of human-AI collaboration. How do you feel about the blending of organic and synthetic in technology? 🤔 Are we ready to navigate the complex moral terrain that comes with these advances? Time to weigh in! Share your thoughts, hit that FOLLOW button, and smash the LIKE for more mind-blowing tech updates. If you're intrigued and hungry for details, check out the source: https://lnkd.in/dwGvFmgi Let's get the conversation started! 🔊 #BrainTech #FutureIsNow #TechTalks

AI Technology Transforming Thoughts into Text: A Breakthrough in Communication 🌟 🚀 Innovative Technology: Researchers from GrapheneX-UTS have developed a portable, non-invasive system converting thoughts into text. 🤝 Assistance for the Disabled: The technology could aid communication for people unable to speak due to illness or injury. 🤖 It's fascinating to see how advancements in AI and neuroscience are paving new ways in communication and human-technology interaction. The GrapheneX-UTS technology, transforming thoughts into text, not only facilitates communication for those with limitations but also paints a future where our interactions with devices are more intuitive and efficient. This is an inspiring example of how innovation can serve societal good, highlighting the immense potential of AI in solving real-world human challenges. If you like what you saw, hit the follow button. If you want to read more, here's a link with video: https://lnkd.in/dxnyuief 📷 Image Credit: DALL-E #AI #Innovation #Neuroscience #Technology #Communication

The Google DeepMind AI model, AlphaFold, is reshaping protein science and how we research in this field. Proteins are the same as micro machines, and its 3D frame builds the base for knowing about the way they perform. In the past, the determination of the shape was painfully drawn with extensive research that lasted for years. Enter AlphaFold! This AI is indeed powerful enough and through it we can predict protein structures with a level of accuracy which is mind-blowing, saving scientists enormous amounts of time and opening new doors for scientific research! It has the potential of making a huge impact in medicine, which among others, will help in tailoring drugs, understanding illnesses and designing new materials for medical purposes. Do you envision the future of medicine to be defined by the discovery of AlphaFold? #AlphaFold #AI #Science #ProteinFolding #Medicine

Neuralink Implants First Brain Chip in Human - A Major Milestone in Brain-Computer Interfaces Key takeaway: Neuralink has achieved a significant breakthrough by implanting its brain chip in a human for the first time. This technology has the potential to revolutionize healthcare and human-computer interaction. Initial focus on individuals with paralysis, enabling them to control devices with their thoughts. Long-term goals include treating neurological disorders and enhancing human capabilities. Future implications might involve seamless brain-computer interaction and a symbiotic relationship with AI. Overall, this is a promising development in the field of neurotechnology, but it's important to remember that it's still in its early stages. Further research and testing are needed before widespread adoption. follow Hancy Khalid Artificial intelligence Enginner for more tech info #ai #tech #neuralnetworks #human #medical #innovation #trend

Descriptive workflow definition languages Today we collect enormous amounts of data. To make these data useful it must be analyzed, either by humans or fed into ML, AI, or even rule-based models. Whatever or whoever performs the analysis, the raw data first has to be extracted from original sources and transformed into something analysis ready. Data acquisition and data processing are workflows, performed by people of different backgrounds, including research assistants and data engineers. All of them know too well that repeatability (getting the same result when re-executing the same workflow in the same environment) and reproducibility (getting the same result when executing the same workflow in a different environment by different actors) of such workflows is an incredible challenge. With the adoption of AI, especially generative AI with their often opaque algorithms, the problem of reproducibility in data preparation for AI models has become more important than ever. Bioinformatics community has long since realized that the only viable way of having a data processing workflow portable and reproducible is to define it in a descriptive domain specific language (DSL). Several such languages are popular among the community members. These languages focus on explicit definition of the workflow topology, inputs, requirements, and outputs and on insulation of these definitions from the logic built into actual processing algorithms. In an effort to promote adoption of the descriptive workflow definition languages paradigm by data scientists and data engineers outside of bioinformatics, I have developed a short training course for Harvard University researchers: Introduction to Data Processing Workflow Languages. A recent post by Heidi Creighton about a reproducibility crisis in science (https://lnkd.in/eE7S_EBs) led me to make the slides for this course (https://lnkd.in/enKfPUWt) and the GitHub repository with the accompanying exercises (https://lnkd.in/eh2SUPES) publicly available. Please, let me know if you find these materials useful.  #reproducibility #ai #machinelearning #datascience #software

Researchers unveil DeepGO-SE, a breakthrough AI tool predicting unknown protein functions! This innovative tool utilizes large language models and logical entailment to analyze and predict functions of uncharacterized proteins, even without database matches. This potentially accelerates drug discovery, metabolic pathway analysis, and understanding of cellular mechanisms. How can this AI tool be utilized to accelerate understanding of complex biological processes and improve human health? #GenerativeAI #AI #Technology #Future #Growth #BioTech #Innovation #Science