For the next year and a half, the camera captured snippets of his life. He crawled around the family’s pets, watched his parents cook, and cried on the front porch with grandma. All the while, the camera recorded everything he heard.
What sounds like a cute toddler home video is actually a daring concept: Can AI learn language like a child? The results could also reveal how children rapidly acquire language and concepts at an early age.
A new study in Science describes how researchers used Sam’s recordings to train an AI to understand language. With just a tiny portion of one child’s life experience over a year, the AI was able to grasp basic concepts—for example, a ball, a butterfly, or a bucket.
This type of AI system is known as a multimodal model. It’s a step beyond just being able to handle text or images like previous algorithms. And it provides a strong hint of where AI may be going next: being able to analyze and respond to real-time information from the outside world.
Although Gemini’s capabilities might not be quite as advanced as they seemed in a viral video, which was edited from carefully curated text and still-image prompts, it is clear that AI systems are rapidly advancing. They are heading towards the ability to handle more and more complex inputs and outputs.
In the dynamic field of Artificial Intelligence (AI), the trajectory from one foundational model to another has represented an amazing paradigm shift. The escalating series of models, including Mamba, Mamba MOE, MambaByte, and the latest approaches like Cascade, Layer-Selective Rank Reduction (LASER), and Additive Quantization for Language Models (AQLM) have revealed new levels of cognitive power. The famous ‘Big Brain’ meme has succinctly captured this progression and has humorously illustrated the rise from ordinary competence to extraordinary brilliance as one delf into the intricacies of each language model.
Mamba is a linear-time sequence model that stands out for its rapid inference capabilities. Foundation models are predominantly built on the Transformer architecture due to its effective attention mechanism. However, Transformers encounter efficiency issues when dealing with long sequences. In contrast to conventional attention-based Transformer topologies, with Mamba, the team introduced structured State Space Models (SSMs) to address processing inefficiencies on extended sequences.
The creation of an artificial intelligence (AI) system that can analyze retinal fundus images to detect chronic kidney disease (CKD) and type 2 diabetes mellitus (T2DM) represents a groundbreaking advancement in medical technology. This AI model, developed using a substantial dataset of retinal images and advanced convolutional neural networks, has demonstrated exceptional accuracy in identifying these conditions. Its capability extends beyond mere detection, as it also shows promise in predicting the progression of these diseases based on retinal imaging and clinical metadata.
A notable innovation of this AI system is its ability to analyze smartphone images. This feature significantly enhances the accessibility of sophisticated diagnostic tools, especially in regions with limited healthcare resources. The AI model paves the way for more widespread and convenient health screenings by enabling ubiquitous smartphone technology for medical imaging. This development is particularly impactful in enhancing healthcare delivery and access, as it brings critical diagnostic capabilities into the hands of more people, even in remote or underserved areas.
The AI’s proficiency in predicting the future development of CKD and T2DM is another aspect of its novelty. This predictive ability is crucial for timely intervention, potentially altering the trajectory of these chronic illnesses. Early detection and management are vital in battling CKD and T2DM, and this AI model’s predictive power could significantly improve patient outcomes.
Micro Electro Mechanical Systems (MEMS) are miniature devices that integrate mechanical elements, sensors, actuators, and electronics on a single silicon chip. These systems serve diverse applications, such as accelerometers in smartphones, gyroscopes in navigation systems, and pressure sensors in medical devices. MEMS devices can detect and respond to environmental changes, enabling the creation of smart, responsive technologies. Their small size, low power consumption, and ability to perform various functions make MEMS crucial in fields like telecommunications, healthcare, automotive, and consumer electronics. Learn more about this tiny machines with this video!
Californian students from the Art Center College had to imagine four concepts of cars of the future for Lincoln, by 2040. One of them, a four-seater sedan, was entitled to the realization of its 1:1 scale model, presented during Monterey Car Week, completed this weekend. Connected, autonomous, shared (“shared”), and electric, as suggested by the acronym “CASE” used by Ford’s luxury brand, which is found in this sedan called “Anniversary”
Bayreuth scientists are investigating the structure and long-term behavior of galaxies using mathematical models based on Einstein’s theory of relativity. Their innovative approach uses a deep neural network to quickly predict the stability of galaxy models. This artificial intelligence-based method enables efficient verification or falsification of astrophysical hypotheses in seconds.
The research objective of Dr. Sebastian Wolfschmidt and Christopher Straub is to investigate the structure and long-term behavior of galaxies. “Since these cannot be fully analyzed by astronomical observations, we use mathematical models of galaxies,” explains Christopher Straub, a doctoral student at the Chair of Mathematics VI at the University of Bayreuth.
“In order to take into account that most galaxies contain a black hole at their center, our models are based on Albert Einstein’s general theory of relativity, which describes gravity as the curvature of four-dimensional spacetime.”
Research conducted by a team of scientists from Kaunas universities, Lithuania, revealed that low-frequency ultrasound influences blood parameters. The findings suggest that ultrasound’s effect on haemoglobin can improve oxygen’s transfer from the lungs to bodily tissues.
The research was undertaken on 300 blood samples collected from 42 pulmonary patients. The samples were exposed to six different low-frequency ultrasound modes at the Institute of Mechatronics of Kaunas University of Technology (KTU).
The changes in 20 blood parameters were registered using the blood analysing equipment at the Lithuanian University of Health Sciences (LSMU) laboratories. For the prediction of ultrasound exposure, artificial intelligence, i.e. analysis of variance (ANOVA), non-parametric Kruskal-Wallis method and machine learning algorithms were applied. The calculations were made at the KTU Artificial Intelligence Centre.
In the XXI century, the world of orbital launchers has started a revolution, a fundamental change of paradigm: the replacement of expendable rockets with reusable ones is well underway. This presentation summarizes the situation at the beginning of year 2024.
A short bio. Alberto Cavallo is an Electrical Engineer, graduated at the Politecnico di Torino in 1985. He began his activity with designing electric systems in Fiat Engineering, the engineering and construction company of the FIAT Group, moving soon to control and automation systems in the same company. He was involved in all business areas of the company, which included revamping and new projects of car factories for the FIAT Group as well as large infrastructures, power and cogeneration plants for external clients. Among the projects of that time were the new FIAT factories in Melfi and Pratola Serra, the high speed railways Torino-Milano and Bologna-Firenze, the district heating system of Torino Sud, combined cycle power plants for several hundred megawatts in Italy and in Brazil. Since Fiat Engineering was transferred from the FIAT Group to a new EPC group and then merged with a large EPC company in Milan, he has been involved in large oil and gas and petrochemical projects all over the world. Besides his professional activity, he has always taken part in several cultural activities. He was a member of the Associations of Alumni of the Liceo Classico Vittorio Alfieri of Turin, active in promoting humanistic culture as well as its connection to the technical and scientific area. He manages his own website www.eurinome.it (in Italian only) about philosophy, science and politics/geopolitics. Due to this he got in contact with Adriano Autino and his TDF, then becoming one of the founding members of Space Renaissance International. Besides several papers in his professional area he has written several articles for his own site, for TDF and SRI, coauthoring the book “Three Theses for the Space Renaissance” with Adriano Autino and Patrick Q. Collins. He is currently member of the Board of SRI.
Welcome to the latest edition of Security & Tech Insights. In this newsletter, predictions on topics of cybersecurity, emerging computing, artificial intelligence, and space will be explored. Thanks for reading and sharing!
