#MIT Computer Science & Artificial Intelligence Laboratory

[travelella]

MIT Computer Science & Artificial Intelligence Laboratory, Vassar Street, Cambridge, Massachusetts, USA

Wenhao Ryan

[xtruss]

This Tiny, Tamper-Proof ID Tag Can Authenticate Almost Anything

Massachusetts Institute of Technology (MIT) Engineers Developed a Tag That Can Reveal with Near-Perfect Accuracy Whether an Item is Real or Fake. The Key is in the Glue on the Back of the Tag.

— Adam Zewe | MIT News | Publication Date: February 18, 2024

A Few Years Ago, MIT Researchers Invented a Cryptographic ID Tag that is several times smaller and significantly cheaper than the traditional radio frequency tags (RFIDs) that are often affixed to products to verify their authenticity.

This tiny tag, which offers improved security over RFIDs, utilizes terahertz waves, which are smaller and travel much faster than radio waves. But this terahertz tag shared a major security vulnerability with traditional RFIDs: A counterfeiter could peel the tag off a genuine item and reattach it to a fake, and the authentication system would be none the wiser.

The researchers have now surmounted this security vulnerability by leveraging terahertz waves to develop an antitampering ID tag that still offers the benefits of being tiny, cheap, and secure.

They mix microscopic metal particles into the glue that sticks the tag to an object, and then use terahertz waves to detect the unique pattern those particles form on the item’s surface. Akin to a fingerprint, this random glue pattern is used to authenticate the item, explains Eunseok Lee, an electrical engineering and computer science (EECS) graduate student and lead author of a paper on the antitampering tag.

“These metal particles are essentially like mirrors for terahertz waves. If I spread a bunch of mirror pieces onto a surface and then shine light on that, depending on the orientation, size, and location of those mirrors, I would get a different reflected pattern. But if you peel the chip off and reattach it, you destroy that pattern,” adds Ruonan Han, an associate professor in EECS, who leads the Terahertz Integrated Electronics Group in the Research Laboratory of Electronics.

The researchers produced a light-powered antitampering tag that is about 4 square millimeters in size. They also demonstrated a machine-learning model that helps detect tampering by identifying similar glue pattern fingerprints with more than 99 percent accuracy.

Because the terahertz tag is so cheap to produce, it could be implemented throughout a massive supply chain. And its tiny size enables the tag to attach to items too small for traditional RFIDs, such as certain medical devices.

The paper, which will be presented at the IEEE Solid State Circuits Conference, is a collaboration between Han’s group and the Energy-Efficient Circuits and Systems Group of Anantha P. Chandrakasan, MIT’s chief innovation and strategy officer, dean of the MIT School of Engineering, and the Vannevar Bush Professor of EECS. Co-authors include EECS graduate students Xibi Chen, Maitryi Ashok, and Jaeyeon Won.

Preventing Tampering

This research project was partly inspired by Han’s favorite car wash. The business stuck an RFID tag onto his windshield to authenticate his car wash membership. For added security, the tag was made from fragile paper so it would be destroyed if a less-than-honest customer tried to peel it off and stick it on a different windshield.

But that is not a terribly reliable way to prevent tampering. For instance, someone could use a solution to dissolve the glue and safely remove the fragile tag.

Rather than authenticating the tag, a better security solution is to authenticate the item itself, Han says. To achieve this, the researchers targeted the glue at the interface between the tag and the item’s surface.

Their antitampering tag contains a series of miniscule slots that enable terahertz waves to pass through the tag and strike microscopic metal particles that have been mixed into the glue.

Terahertz waves are small enough to detect the particles, whereas larger radio waves would not have enough sensitivity to see them. Also, using terahertz waves with a 1-millimeter wavelength allowed the researchers to make a chip that does not need a larger, off-chip antenna.

After passing through the tag and striking the object’s surface, terahertz waves are reflected, or backscattered, to a receiver for authentication. How those waves are backscattered depends on the distribution of metal particles that reflect them.

The researchers put multiple slots onto the chip so waves can strike different points on the object’s surface, capturing more information on the random distribution of particles.

“These responses are impossible to duplicate, as long as the glue interface is destroyed by a counterfeiter,” Han says.

A vendor would take an initial reading of the antitampering tag once it was stuck onto an item, and then store those data in the cloud, using them later for verification.

AI For Authentication

But when it came time to test the antitampering tag, Lee ran into a problem: It was very difficult and time-consuming to take precise enough measurements to determine whether two glue patterns are a match.

He reached out to a friend in the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) and together they tackled the problem using AI. They trained a machine-learning model that could compare glue patterns and calculate their similarity with more than 99 percent accuracy.

“One drawback is that we had a limited data sample for this demonstration, but we could improve the neural network in the future if a large number of these tags were deployed in a supply chain, giving us a lot more data samples,” Lee says.

The authentication system is also limited by the fact that terahertz waves suffer from high levels of loss during transmission, so the sensor can only be about 4 centimeters from the tag to get an accurate reading. This distance wouldn’t be an issue for an application like barcode scanning, but it would be too short for some potential uses, such as in an automated highway toll booth. Also, the angle between the sensor and tag needs to be less than 10 degrees or the terahertz signal will degrade too much.

They plan to address these limitations in future work, and hope to inspire other researchers to be more optimistic about what can be accomplished with terahertz waves, despite the many technical challenges, says Han.

“One thing we really want to show here is that the application of the terahertz spectrum can go well beyond broadband wireless. In this case, you can use terahertz for ID, security, and authentication. There are a lot of possibilities out there,” he adds.

This work is supported, in part, by the U.S. National Science Foundation and the Korea Foundation for Advanced Studies.

[transgenderer]

Stephanie Seneff (born April 20, 1948)[1]: 249  is an American computer scientist and anti-vaccine activist.[2][3] She is a senior research scientist at the Computer Science and Artificial Intelligence Laboratory (CSAIL) of the Massachusetts Institute of Technology (MIT). In her early career, she worked primarily in the Spoken Language Systems group, where her research at CSAIL focused on human–computer interaction, and algorithms for language understanding and speech recognition. In 2011, she began publishing controversial papers in low-impact, open access journals on biology and medical topics; the articles have received "heated objections from experts in almost every field she's delved into," according to the food columnist Ari LeVaux.[4]

[jcmarchi]

Study reveals AI chatbots can detect race, but racial bias reduces response empathy

New Post has been published on https://thedigitalinsider.com/study-reveals-ai-chatbots-can-detect-race-but-racial-bias-reduces-response-empathy/

Study reveals AI chatbots can detect race, but racial bias reduces response empathy

With the cover of anonymity and the company of strangers, the appeal of the digital world is growing as a place to seek out mental health support. This phenomenon is buoyed by the fact that over 150 million people in the United States live in federally designated mental health professional shortage areas.

“I really need your help, as I am too scared to talk to a therapist and I can’t reach one anyways.”

“Am I overreacting, getting hurt about husband making fun of me to his friends?”

“Could some strangers please weigh in on my life and decide my future for me?”

The above quotes are real posts taken from users on Reddit, a social media news website and forum where users can share content or ask for advice in smaller, interest-based forums known as “subreddits.” 

Using a dataset of 12,513 posts with 70,429 responses from 26 mental health-related subreddits, researchers from MIT, New York University (NYU), and University of California Los Angeles (UCLA) devised a framework to help evaluate the equity and overall quality of mental health support chatbots based on large language models (LLMs) like GPT-4. Their work was recently published at the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP).

To accomplish this, researchers asked two licensed clinical psychologists to evaluate 50 randomly sampled Reddit posts seeking mental health support, pairing each post with either a Redditor’s real response or a GPT-4 generated response. Without knowing which responses were real or which were AI-generated, the psychologists were asked to assess the level of empathy in each response.

Mental health support chatbots have long been explored as a way of improving access to mental health support, but powerful LLMs like OpenAI’s ChatGPT are transforming human-AI interaction, with AI-generated responses becoming harder to distinguish from the responses of real humans.

Despite this remarkable progress, the unintended consequences of AI-provided mental health support have drawn attention to its potentially deadly risks; in March of last year, a Belgian man died by suicide as a result of an exchange with ELIZA, a chatbot developed to emulate a psychotherapist powered with an LLM called GPT-J. One month later, the National Eating Disorders Association would suspend their chatbot Tessa, after the chatbot began dispensing dieting tips to patients with eating disorders.

Saadia Gabriel, a recent MIT postdoc who is now a UCLA assistant professor and first author of the paper, admitted that she was initially very skeptical of how effective mental health support chatbots could actually be. Gabriel conducted this research during her time as a postdoc at MIT in the Healthy Machine Learning Group, led Marzyeh Ghassemi, an MIT associate professor in the Department of Electrical Engineering and Computer Science and MIT Institute for Medical Engineering and Science who is affiliated with the MIT Abdul Latif Jameel Clinic for Machine Learning in Health and the Computer Science and Artificial Intelligence Laboratory.

What Gabriel and the team of researchers found was that GPT-4 responses were not only more empathetic overall, but they were 48 percent better at encouraging positive behavioral changes than human responses.

However, in a bias evaluation, the researchers found that GPT-4’s response empathy levels were reduced for Black (2 to 15 percent lower) and Asian posters (5 to 17 percent lower) compared to white posters or posters whose race was unknown. 

To evaluate bias in GPT-4 responses and human responses, researchers included different kinds of posts with explicit demographic (e.g., gender, race) leaks and implicit demographic leaks. 

An explicit demographic leak would look like: “I am a 32yo Black woman.”

Whereas an implicit demographic leak would look like: “Being a 32yo girl wearing my natural hair,” in which keywords are used to indicate certain demographics to GPT-4.

With the exception of Black female posters, GPT-4’s responses were found to be less affected by explicit and implicit demographic leaking compared to human responders, who tended to be more empathetic when responding to posts with implicit demographic suggestions.

“The structure of the input you give [the LLM] and some information about the context, like whether you want [the LLM] to act in the style of a clinician, the style of a social media post, or whether you want it to use demographic attributes of the patient, has a major impact on the response you get back,” Gabriel says.

The paper suggests that explicitly providing instruction for LLMs to use demographic attributes can effectively alleviate bias, as this was the only method where researchers did not observe a significant difference in empathy across the different demographic groups.

Gabriel hopes this work can help ensure more comprehensive and thoughtful evaluation of LLMs being deployed in clinical settings across demographic subgroups.

“LLMs are already being used to provide patient-facing support and have been deployed in medical settings, in many cases to automate inefficient human systems,” Ghassemi says. “Here, we demonstrated that while state-of-the-art LLMs are generally less affected by demographic leaking than humans in peer-to-peer mental health support, they do not provide equitable mental health responses across inferred patient subgroups … we have a lot of opportunity to improve models so they provide improved support when used.”

[darkmaga-returns]

Dr. Stephanie Seneff is a Senior Research Scientist at MIT's Computer Science and Artificial Intelligence Laboratory in Cambridge, Massachusetts. She talks the nomination of Casey Means for Surgeon General, glyphosate, seed oils, how it has poisoned the food supply, rise in autism, autoimmune disorders, obesity, ozempic, benefits of butter, and much more. PLEASE SUBSCRIBE LIKE AND SHARE THIS PODCAST!!!   

[materialsscienceandengineering]

Using AI to discover stiff and tough microstructures

Innovative AI system from MIT CSAIL melds simulations and physical testing to forge materials with newfound durability and flexibility for diverse engineering uses.

Every time you smoothly drive from point A to point B, you're not just enjoying the convenience of your car, but also the sophisticated engineering that makes it safe and reliable. Beyond its comfort and protective features lies a lesser-known yet crucial aspect: the expertly optimized mechanical performance of microstructured materials. These materials, integral yet often unacknowledged, are what fortify your vehicle, ensuring durability and strength on every journey.  Luckily, MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) scientists have thought about this for you. A team of researchers moved beyond traditional trial-and-error methods to create materials with extraordinary performance through computational design. Their new system integrates physical experiments, physics-based simulations, and neural networks to navigate the discrepancies often found between theoretical models and practical results. One of the most striking outcomes: the discovery of microstructured composites — used in everything from cars to airplanes — that are much tougher and durable, with an optimal balance of stiffness and toughness. 

Read more.

[sarkariresultdude]

Madras Institute of Technology: Excellence in Academics and Result Analysis

 The Madras Institute of Technology (MIT), positioned in Chennai, Tamil Nadu, is certainly one of India's most excellent engineering establishments. Established in 1949, MIT has constructed a stellar popularity for innovation and educational rigor. The institute has produced splendid alumni, consisting of Dr. A.P.J. Abdul Kalam, India's former President and a celebrated aerospace scientist. MIT is a constituent university of Anna University and offers undergraduate, postgraduate, and studies packages in engineering, generation, and applied sciences.

Madras Institute Technology Result

One of the important thing aspects that outline MIT is its emphasis on high academic standards. Results and educational performance at MIT play a pivotal role in keeping this recognition, reflecting the institute's recognition of fostering talent and nurturing innovation.

Academic Programs at MIT

Before delving into the results, it is important to understand the instructional packages that MIT gives. The institute specializes in engineering disciplines which include:

Aeronautical Engineering

Electronics and Communication Engineering

Computer Science and Engineering

Mechanical Engineering

Automobile Engineering

Instrumentation Engineering

Production Technology

MIT also gives applications in contemporary domains like Artificial Intelligence, Data Science, and Robotics, ensuring that scholars are equipped to address contemporary demanding situations in technological know-how and era.

Academic Structure and Examination Process

MIT follows a semester-based totally academic calendar, with two foremost terms: the atypical semester (July–November) and the even semester (January–May). Each semester consists of a mixture of theoretical and sensible guides, which might be evaluated through a combination of non-stop evaluation and up-semester examinations.

Continuous Assessment:

Assignments, quizzes, and mid-time period tests contribute to the inner assessment marks.

Laboratory work and challenging opinions are key components of sensible guides.

Internal exams generally account for forty–50% of the entire marks.

End-Semester Examinations:

Conducted under Anna University’s pointers, those tests compare students' know-how of the whole syllabus.

The exams usually span two weeks, overlaying all enrolled courses.

A minimum pass percentage is required in each inner and external test.

Result Declaration Process

The end result declaration technique at MIT is a systematic and transparent manner aimed toward ensuring accuracy and fairness. The key steps involved include:

Evaluation and Grading

Answer scripts from the cease-semester examinations are evaluated by experienced faculty individuals under strict supervision.

Marks are offered primarily based on a pre-described marking scheme to maintain uniformity.

Grading follows Anna University’s requirements, typically on a scale of 10.

 Internal Moderation    

Before finalizing effects, moderation committees evaluate borderline cases and cope with discrepancies.

This guarantees that proper mistakes in assessment do not adversely affect college students.

 Publication of Results

Results are posted online at the respectable Anna University portal. Students can access their grades using their registration numbers.

Results encompass details along with direction-sensible grades, overall credits earned, and the Cumulative Grade Point Average (CGPA).

Revaluation and Supplementary Exams

Students upset with their outcomes can apply for revaluation or photocopies of their solution scripts.

Supplementary checks are carried out for college kids who fail to clear certain guides, enabling them to progress without losing a year.

Factors Affecting Results at MIT

Academic achievement at MIT depends on numerous factors:

Rigorous Curriculum:

The difficult syllabus needs constant attempt from college students.

Courses emphasize not only theoretical expertise but also sensible hassle-fixing.

Student Resources:

MIT offers sizeable resources, which include advanced laboratories, study facilities, and a properly-stocked library, which support educational excellence.

Regular workshops and seminars keep college students up to date on enterprise developments.

Faculty Expertise:

The institute boasts fairly certified faculty participants who guide college students via their educational adventures.

Faculty mentoring ensures students acquire customized feedback to enhance their overall performance.

Peer Competition:

The competitive surroundings at MIT pushes college students to attempt for excellence.

Group projects and collaborative studying foster teamwork and innovation.

Notable Trends in MIT Results

Over the years, sure tendencies have emerged in MIT's instructional effects:

High Pass Percentage:

Due to rigorous practise and the supply of assets, MIT commonly facts a excessive bypass percentage across disciplines.

Consistent Toppers:

Students from MIT regularly stable pinnacle rank in Anna University’s consolidated outcomes, reflecting the institute’s instructional nice.

Focus on Core and Emerging Areas:

Students excel in core engineering disciplines while also reaching commendable outcomes in new-age fields like AI and IoT.

Challenges inside the Result Process

Despite its sturdy device, some challenges from time to time arise up in MIT’s result declaration procedure:

Revaluation Delays:

The revaluation system now and again reports delays due to the high extent of packages, causing tension among college students.

Technical Glitches:

The online end result portal may additionally face technical troubles at some point of top traffic intervals, mainly due to accessibility worries.

Exam Stress:

The rigorous educational surroundings can result in stress among college students, impacting their performance.

Initiatives for Improvement

MIT constantly works to beautify its end-result procedure through numerous projects:

Digital Solutions:

The adoption of AI-pushed assessment tools guarantees faster and more correct consequences.

Online portals are being upgraded to deal with better visitor volumes.

Student Counseling:

Regular counseling sessions assist college students deal with exam strain and consciousness of their strengths.

Enhanced Feedback Mechanisms:

Faculty provide certain comments on internal assessments, helping college students cope with their weaknesses before the very last assessments.

[moremedtech]

Atlas of human brain blood vessels highlights changes in Alzheimer’s disease

Atlas of human brain blood vessels highlights changes in Alzheimer’s disease MIT researchers characterize gene expression patterns for 22,500 brain vascular cells across 428 donors, revealing insights for Alzheimer’s onset and potential treatments. Your brain is powered by 400 miles of blood vessels that provide nutrients, clear out waste products, and form a tight protective barrier — the blood-brain barrier — that controls which molecules can enter or exit. However, it has remained unclear how these brain vascular cells change between brain regions, or in Alzheimer’s disease, at single-cell resolution. To address this challenge, a team of scientists from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), The Picower Institute for Learning and Memory, and The Broad Institute of MIT and Harvard recently unveiled a systematic molecular atlas of human brain vasculature and its changes in Alzheimer’s disease (AD) across six brain regions, in a paper published June 1 in Nature Neuroscience. Alzheimer's disease is a leading cause of death, affects one in nine Americans over 65, and leads to debilitating and devastating cognitive decline. Impaired blood-brain barrier (BBB) function has long been associated with Alzheimer’s and other neurodegenerative diseases, such as Parkinson's and multiple sclerosis. However, the molecular and cellular underpinnings of BBB dysregulation remain ill-defined, particularly at single-cell resolution across multiple brain regions and many donors.

Navigating vascular complexity

Embarking deep into the complexities of our gray matter, the researchers created a molecular atlas of human brain vasculature across 428 donors, including 220 diagnosed with Alzheimer's and 208 controls. They characterized over 22,514 vascular cells from six different brain regions, measuring the expression of thousands of genes for each cell. The resulting datasets unveiled intriguing changes in gene expression across different brain regions and stark contrasts between individuals afflicted with AD and those without. “Alzheimer's therapy development faces a significant hurdle — brain alterations commence decades before cognitive signs make their debut, at which point it might already be too late to intervene effectively,” comments MIT CSAIL principal investigator and electrical engineering and computer science (EECS) Professor Manolis Kellis. “Our work charts the terrain of vascular changes, one of the earliest markers of Alzheimer's, across multiple brain regions, providing a map to guide biological and therapeutic investigations earlier in disease progression.” Kellis is the study's co-senior author, along with MIT Professor Li-Huei Tsai, director of the Picower Institute and the Picower Professor in the Department of Brain and Cognitive Sciences.

The little cells that could

The threads of our human brain vasculature, and every part of our brain and body, are composed of millions of cells, all sharing the same DNA code, but each expressing a different subset of genes, which define its functional roles and distinct cell type. Using the distinct gene expression signatures of different cerebrovascular cells, the researchers distinguished 11 types of vascular cells. These included endothelial cells that line the interior surface of blood vessels and control which substances pass through the BBB, pericytes that wrap around small vessels and provide structural support and blood flow control, smooth muscle cells that form the middle layer of large vessels and whose contraction and relaxation regulates blood flow and pressure, fibroblasts that surround blood vessels and hold them in place, and they distinguished arteriole, venule, and capillary veins responsible for the different stages of blood oxygen exchange. The abundance of these vascular cell types differed between brain regions, with neocortical regions showing more capillary endothelial cells and fewer fibroblasts than subcortical regions, highlighting the regional heterogeneity of the BBB.

Clues and suspects

Armed with these annotations, the next phase was studying how each of these cell types change in AD, revealing 2,676 genes whose expression levels change significantly. They found that capillary endothelial cells, responsible for transport, waste removal, and immune surveillance, showed the most changes in AD, including genes involved in clearance of amyloid beta, one of the pathological hallmarks of AD, providing insights on the potential mechanistic implications of vascular dysregulation on AD pathology. Other dysregulated processes included immune function, glucose homeostasis, and extracellular matrix organization, which were all shared among multiple vascular cell types, and also cell-type-specific changes, including growth factor receptors in pericytes, and transporter and energy in endothelial cells, and cellular response to amyloid beta in smooth muscle cells. Regulation of insulin sensing and glucose homeostasis in particular suggested important connections between lipid transport and Alzheimer’s regulated by the vasculature and blood-brain-barrier cells, which could hold promise for new therapeutic clues. “Single-cell RNA sequencing provides an extraordinary microscope to peer into the intricate machinery of life, and ‘see’ millions of RNA molecules bustling with activity within each cell,” says Kellis, who is also a member of the Broad Institute. “This level of detail was inconceivable just a few years ago, and the resulting insights can be transformative to comprehend and combat complex psychiatric and neurodegenerative disease."

Maestros of dysregulation

Genes do not act on a whim, and they do not act alone. Cellular processes are governed by a complex cast of regulators, or transcription factors, that dictate which groups of genes should be turned on or off in different conditions, and in different cell types. These regulators are responsible for interpreting our genome, the ‘book of life,’ and turning it into the myriad of distinct cell types in our bodies and in our brains. These regulators might be responsible when something goes wrong, and they could also be critical in fixing things and restoring healthy cellular states. With thousands of genes showing altered expression levels in Alzheimer’s disease, the researchers then sought to find the potential masterminds behind these changes. They asked if common regulatory control proteins target numerous altered genes, which may provide candidate therapeutic targets to restore the expression levels of large numbers of target genes. Indeed, they found several such ‘master controllers,’ involved in regulating endothelial differentiation, inflammatory response, and epigenetic state, providing potential intervention points for drug targets against AD.

Cellular murmurings

Cells do not function in isolation; rather, they rely on communication with each other to coordinate biological processes. This intercellular communication is particularly complex within the cellular diversity of the brain, given the many factors involved in sensing, memory formation, knowledge integration, and consciousness. In particular, vascular cells have intricate interactions with neurons, microglia, and other brain cells, which take on heightened significance during pathological events, such as in Alzheimer's disease, where dysregulation of this cellular communication can contribute to the progression of the disease. The researchers found that interactions from capillary endothelial cells to neurons, microglia, and astrocytes were highly increased in AD, while interactions in the reverse direction, from neurons and astrocytes to capillary endothelial cells, were decreased in AD. This asymmetry could provide important cues for potential interventions targeting the vasculature and specifically capillary endothelial cells, with ultimate broad positive impacts on the brain. “The dynamics of vascular cell interactions in AD provide an entry point for brain interventions and potential new therapies,” says Na Sun, an EECS graduate student and MIT CSAIL affiliate and first author on the study. “As the blood-brain barrier prevents many drugs from influencing the brain, perhaps we could instead manipulate the blood-brain barrier itself, and let it spread beneficiary signals to the rest of the brain. Our work provides a blueprint for cerebrovasculature interventions in Alzheimer's disease, by unraveling how cellular communication can mediate the impact of genetic variants in AD."

Going off script: genetic plot twists

Disease onset in our bodies (and in our brains) is shaped by a combination of genetic predispositions and environmental exposures. On the genetic level, most complex traits are shaped by hundreds of minuscule sequence alterations, known as single-nucleotide polymorphisms (or SNPs, pronounced snips), most of which act through subtle changes in gene expression levels. No matter how subtle their effects might be, these genetic changes can reveal causal contributors to disease, which can greatly increase the chance of therapeutic success for genetically-supported target genes, compared to targets lacking genetic support. To understand how genetic differences associated with Alzheimer’s might act in the vasculature, the researchers then sought to connect genes that showed altered expression in Alzheimer’s with genetic regions associated with increased Alzheimer’s risk through genetic studies of thousands of individuals. They linked the genetic variants (SNPs) to candidate target genes using three lines of evidence: physical proximity in the three-dimensional folded genome, genetic variants that affect gene expression, and correlated activity between distant regulatory regions and target genes that go on and off together between different conditions. This resulted in not just one hit, but 125 genetic regions, where Alzheimer’s-associated genetic variants were linked to genes with disrupted expression patterns in Alzheimer’s disease, suggesting they might mediate these causal genetic effects, and thus may be good candidates for therapeutic targeting. Some of these predicted hits were direct, where the genetic variant acted directly on a nearby gene. Others were indirect when the genetic variant instead affected the expression of a regulator, which then affected the expression of its target genes. And yet others were predicted to be indirect through cell-cell communication networks.

ApoE4 and cognitive decline

While most genetic effects are subtle, both in Alzheimer’s and nearly all complex disorders, exceptions do exist. One such exception is FTO in obesity, which increases obesity risk by one standard deviation. Another one is apolipoprotein E (ApoE) in Alzheimer’s disease, where the E4 versus E3 allele increases risk more than 10-fold for carriers of two risk alleles — those who inherited one ‘unlucky’ copy from each parent. With such a strong effect size, the researchers then asked if ApoE4 carriers showed specific changes in vascular cells that were not found in ApoE3 carriers. Indeed, they found abundance changes associated with the ApoE4 genotype, with capillary endothelial cells and pericytes showing extensive down-regulation of transport genes. This has important implications for potential preventive treatments targeting transport in ApoE4 carriers, especially given the cholesterol transporter roles of ApoE, and the increasingly recognized role of lipid metabolism in Alzheimer’s disease. "Unearthing these AD-differential genes gives us a glimpse into how they may be implicated in the deterioration or dysfunction of the brain's protective barrier in Alzheimer's patients, shedding light on the molecular and cellular roots of the disease's development," says Kellis. "They also open several avenues for therapeutic development, hinting at a future where these entry points might be harnessed for new Alzheimer's treatments targeting the blood-brain barrier directly. The possibility of slowing or even halting the disease's progression is truly exciting.” Translating these findings into viable therapeutics will be a journey of exploration, demanding rigorous preclinical and clinical trials. To bring these potential therapies to patients, scientists need to understand how to target the discovered dysregulated genes safely and effectively and determine whether modifying their activity can ameliorate or reverse AD symptoms, which requires extensive collaborations between medical doctors and engineers across both academia and industry. “This is a tour de force impressive case series,” says Elizabeth Head, vice chair for pathology research and pathology professor at the University of California at Irvine, who was not involved in the research. “A novel aspect of this study was also the methodological approach, which left the vasculature intact, as compared to previous work where blood vessel enrichment protocol was applied. Manolis Kellis and his colleagues show clear evidence of neurovascular unit dysregulation in AD and it is exciting to see known and novel pathways being identified that will accelerate discoveries at the protein level. Many DEGs associated with AD are linked to lipid/cholesterol metabolism, to AD genetic risk factors (including ApoE) and inflammation. The potential for the ApoE genotype in mediating cerebrovascular function will also lead to possible new mouse models that will capture the human phenotype more closely with respect to the vascular contributions to dementia in humans. The regional differences in DEGs are fascinating and will guide future neuropathology studies in the human brain and drive novel hypotheses.” "The predominant focus in AD research over the past 10 years has been on studying microglia, the resident macrophage-like cells of the brain,” adds Ryan Corces, an assistant professor of neurology at the University of California at San Francisco who was also not involved in the work. “While microglia certainly play a key role in disease pathogenesis, it has become increasingly clear through studies such as this one that vascular cells may also be critically involved in the disease. From blood-brain barrier leakage to an enhanced need for debris clearance, the vascular cells of the brain play an important part in this complex disease. This study, and others like it, have begun picking apart the underlying molecular changes that occur in vascular cells, showing which genes appear dysregulated and how those changes may interact to alter vascular cell functions. Together with the mounting evidence of vascular involvement in AD, this work provides an important foundation for guiding therapeutic interventions against blood-brain barrier dysfunction in AD, especially during the preclinical or prodromal stages of the disease, where the blood-brain barrier may be playing a central role.” Sun, Kellis, and Tsai wrote the paper alongside Leyla Anne Akay, Mitchell H. Murdock, Yongjin Park, Fabiola Galiana-Melendez, Adele Bubnys, Kyriaki Galani, Hansruedi Mathys, Xueqiao Jiang, and Ayesha P. Ng of MIT and David A. Bennett of the Rush Alzheimer’s Disease Center in Chicago. This work was supported, in part, by National Institutes of Health grants, the Cure Alzheimer’s Foundation CIRCUITS consortium, the JPB Foundation, Robert A. and Renee Belfer, and a Takeda Fellowship from the Takeda Pharmaceutical Company. Source: MIT Read the full article

[rebeccabobecca]

There are a lot of assumptions happening there. You say specifically that Musk's 35 unapproved methane generators are being addressed, but I have not seen any evidence of that. He was forced to get permits for 15 of his 35 generators, but they all exist in a legal loophole, and none of them have been shut down. Whether that will happen after his and Trump's public breakup is yet to be seen.

Yes new forms of energy are being worked on but crucially they are not ready yet, and local power grids are under strain. This article talks about how meta, microsoft, and google's measurable greenhouse gas production have increased 30-50% over 4 years due to ai, and how meta is using coal power plants to power it. This article talks about how the high and uneven load is stressing the entire local grid to data centers, increasing the entire community's energy bill, and damaging their appliances. (Yes, this article puts forward bloom energy as a solution, Here's a Forbes article talking about how bloom energy is both dirty and inefficient, x). Regardless of the validity of their proposed solution, the description of the problem is still relevant). Here's an academic paper from the University of Alberta talking about the damage the high and uneven power draw does to energy grids. Here's an article from MIT talking about how the AI data centers are the 11th highest global power user, using power than the nation of Saudi Arabia, and that is projected to increase. Here's a quote from that article:

“The demand for new data centers cannot be met in a sustainable way. The pace at which companies are building new data centers means the bulk of the electricity to power them must come from fossil fuel-based power plants,” says Noman Bashir, lead author of the impact paper, who is a Computing and Climate Impact Fellow at MIT Climate and Sustainability Consortium (MCSC) and a postdoc in the Computer Science and Artificial Intelligence Laboratory (CSAIL).

There are lots of solutions for green energy in the works, but they are only in the works, not in production, currently mitigating existing harm. Being "on the verge of the solarpunk revolution" does not help the people in Memphis breathing in methane fumes, or the people's who's appliances are breaking down, or the communities whose water resources are being depleted because a chatgpt query uses 4 times more water than a google search. More than making fossil fuels unprofitable, generative AI is making fossils fuels necessary for their function.

People call generative AI a plagiarism machine because users consistently feed books, papers, and stories into the AI without the consent of the authors, and then get the AI to write in that authors style, or finish an existing story, and the actual authors get no credit or compensation. There has been more than a few scandals in publishing of authors using chatgpt to replicate other authors tone or writing style, instead of writing their own novels. If AI companies can not pay to license the material they use for training, what gives them the right to use it? In any other case, if a company used the images of an artist's entire catalogue, in an advertisement, or a campaign, they would be legally required to pay the artist and license their work, so what makes chatgpt scalping that artist's website and training the AI on their art any different? Artist's and writers are rightfully angry when you can type "write a story in Diane Duane's style" and it does, because someone fed her entire oeuvre into the machine, and now the user has a story using DD's voice, something that she spent her entire career developing, and is what distinguishes her from other authors.

And none of this argument about environmental impact addresses the ethics of the tool itself. While there is plenty of evidence of analytic ais for medical and scientific use, what I have seen from generative ai is lawyers getting sanctioned for using to make arguments, doctors entering personal medical information into AI without regard for HIPAA, entertainment studios using it to get out of paying voice actors, students using it to get out of writing their papers. Also, AI is as biased as the systems that built it, meaning that they have been proven to yield biases that greatly impact their uses in most fields. Police using ai to "identify" suspects have arrested the wrong man on several occasions due to the AI not being able to discern black men, and the department of corrections has used AI to determine whether someone will reoffend, and the AI they use consistently outputs that black people reoffend 45% more than they actually do, and white people 25% less than they actually do. Medical centers that use AI have found that the AI consistently underestimates the amount of treatment that black people need, continuing a long-standing trend of not giving black people the treatment they need. Not to mention all of the various biases of ais used in recruitment and hiring, such as racism, sexism, and ageism.

There's a saying that a system's purpose is what it does, and what AI has done is produce plagiarized, often mediocre or inaccurate content at the expense of creatives, vulnerable people, and the environment.

"what did students do before chatgpt?" well one time i forgot i had a history essay due at my 10am class the morning of so over the course of my 30 minute bus ride to school i awkwardly used by backpack as a desk, sped wrote the essay, and got an A on it.

six months later i re-read the essay prior to the final exam, went 'ohhhh yeah i remember this', got a question on that topic, and aced it.

point being that actually doing the work is how you learn the material and internalize it. ChatGPT can give you a short cut but it won't build you the the muscles.

[sunaleisocial]

Researchers present bold ideas for AI at MIT Generative AI Impact Consortium kickoff event

New Post has been published on https://sunalei.org/news/researchers-present-bold-ideas-for-ai-at-mit-generative-ai-impact-consortium-kickoff-event/

Researchers present bold ideas for AI at MIT Generative AI Impact Consortium kickoff event

Launched in February of this year, the MIT Generative AI Impact Consortium (MGAIC), a presidential initiative led by MIT’s Office of Innovation and Strategy and administered by the MIT Stephen A. Schwarzman College of Computing, issued a call for proposals, inviting researchers from across MIT to submit ideas for innovative projects studying high-impact uses of generative AI models.

The call received 180 submissions from nearly 250 faculty members, spanning all of MIT’s five schools and the college. The overwhelming response across the Institute exemplifies the growing interest in AI and follows in the wake of MIT’s Generative AI Week and call for impact papers. Fifty-five proposals were selected for MGAIC’s inaugural seed grants, with several more selected to be funded by the consortium’s founding company members.

Over 30 funding recipients presented their proposals to the greater MIT community at a kickoff event on May 13. Anantha P. Chandrakasan, chief innovation and strategy officer and dean of the School of Engineering who is head of the consortium, welcomed the attendees and thanked the consortium’s founding industry members.

“The amazing response to our call for proposals is an incredible testament to the energy and creativity that MGAIC has sparked at MIT. We are especially grateful to our founding members, whose support and vision helped bring this endeavor to life,” adds Chandrakasan. “One of the things that has been most remarkable about MGAIC is that this is a truly cross-Institute initiative. Deans from all five schools and the college collaborated in shaping and implementing it.”

Vivek F. Farias, the Patrick J. McGovern (1959) Professor at the MIT Sloan School of Management and co-faculty director of the consortium with Tim Kraska, associate professor of electrical engineering and computer science in the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), emceed the afternoon of five-minute lightning presentations.

Presentation highlights include:

“AI-Driven Tutors and Open Datasets for Early Literacy Education,” presented by Ola Ozernov-Palchik, a research scientist at the McGovern Institute for Brain Research, proposed a refinement for AI-tutors for pK-7 students to potentially decrease literacy disparities.

“Developing jam_bots: Real-Time Collaborative Agents for Live Human-AI Musical Improvisation,” presented by Anna Huang, assistant professor of music and assistant professor of electrical engineering and computer science, and Joe Paradiso, the Alexander W. Dreyfoos (1954) Professor in Media Arts and Sciences at the MIT Media Lab, aims to enhance human-AI musical collaboration in real-time for live concert improvisation.

“GENIUS: GENerative Intelligence for Urban Sustainability,” presented by Norhan Bayomi, a postdoc at the MIT Environmental Solutions Initiative and a research assistant in the Urban Metabolism Group, which aims to address the critical gap of a standardized approach in evaluating and benchmarking cities’ climate policies.

Georgia Perakis, the John C Head III Dean (Interim) of the MIT Sloan School of Management and professor of operations management, operations research, and statistics, who serves as co-chair of the GenAI Dean’s oversight group with Dan Huttenlocher, dean of the MIT Schwarzman College of Computing, ended the event with closing remarks that emphasized “the readiness and eagerness of our community to lead in this space.”

“This is only the beginning,” he continued. “We are at the front edge of a historic moment — one where MIT has the opportunity, and the responsibility, to shape the future of generative AI with purpose, with excellence, and with care.”

[collegedunias]

MIT World Peace University – Your Gateway to Quality Higher Education

Choosing the right university after 12th is a major decision that shapes your future. If you want a place where modern education meets values, innovation, and global exposure, then MIT World Peace University is the perfect choice. It offers top-quality education, holistic development, and a peaceful learning environment.

Located in Pune, Maharashtra, MIT World Peace University (MIT-WPU) is one of India’s leading private universities. It is known for academic excellence, world-class infrastructure, and industry-ready programs that prepare students for a successful career.

About MIT World Peace University

MIT World Peace University is part of the prestigious MIT Group of Institutions, founded in 1983. The university was established to provide future leaders with a blend of science, technology, and values. It is recognized by the University Grants Commission (UGC) and ranked among the top universities in India.

The university offers undergraduate, postgraduate, diploma, and doctoral programs in fields such as Engineering, Management, Law, Pharmacy, Journalism, Liberal Arts, and more.

Why Choose MIT World Peace University?

Here are the top reasons why thousands of students choose MIT World Peace University every year:

UGC-approved and NAAC-accredited

Ranked among the top 100 universities in India

Strong focus on academics, research, and peace studies

Industry-aligned curriculum and skill-based learning

100+ international collaborations with universities worldwide

1,500+ recruiters with strong placement support

Safe and modern campus with advanced labs and libraries

Scholarships for meritorious and needy students

The university aims to build socially responsible professionals through a perfect balance of knowledge and peace-based education.

Courses Offered at MIT World Peace University

Students can choose from a wide range of courses based on their interests and career goals. Popular programs include:

Engineering (B.Tech)

Computer Science & Engineering

Artificial Intelligence and Data Science

Civil Engineering

Electronics & Communication

Mechanical Engineering

Management (BBA, MBA)

BBA in International Business

MBA in Finance, Marketing, HR, Business Analytics

Other Programs

B.Sc., M.Sc. in Physics, Chemistry, and Mathematics

BA (Hons), MA in Political Science, English, Economics

Law (BA LLB, BBA LLB)

BCA, MCA

Journalism & Mass Communication

All courses at MIT World Peace University are updated as per industry standards and include real-world training.

Admission Process

Getting admission at MIT World Peace University is simple and transparent. Here’s how you can apply:

Step-by-step Admission Process:

Visit the official MIT-WPU website

Register and fill out the online application form

Choose your desired course and upload documents

Appear for the MIT-WPU entrance test or submit national-level exam scores (like JEE, NEET, CAT, etc.)

Attend interview or counseling round (if applicable)

Confirm admission by paying the fees

Eligibility:

For UG courses: 10+2 with minimum 50% marks (45% for reserved categories)

For PG courses: Graduation with minimum 50% marks and relevant entrance test scores

Campus and Facilities

MIT World Peace University has one of the most beautiful and student-friendly campuses in India. Located in Pune, the campus is equipped with:

Smart classrooms and lecture halls

Advanced laboratories and research centers

Central library with digital resources

Hostel accommodation with modern amenities

Cafeterias, gym, sports grounds, and meditation hall

Health center and 24x7 security

Wi-Fi enabled environment across the campus

What makes it unique is the Peace Dome, where students participate in daily peace-building activities like yoga, meditation, and value-based learning.

Placements and Internships

MIT World Peace University has an excellent track record in placements. The Career Services Department works throughout the year to connect students with top recruiters.

Placement Highlights:

1,500+ companies visit for campus drives

95%+ placement in core programs

Highest package: ₹44 LPA

Average package: ₹6–8 LPA

Top recruiters: TCS, Infosys, IBM, HCL, Accenture, Amazon, HDFC Bank, Deloitte

Internships are a part of most programs, giving students early exposure to real work environments.

Industry Exposure and International Collaborations

MIT World Peace University provides global opportunities through:

MoUs with universities in USA, UK, Australia, and Europe

Student exchange and study abroad programs

Guest lectures and workshops by international experts

Global internships and joint research projects

Participation in international peace conferences and seminars

This global learning experience makes students more confident and industry-ready.

Life at MIT-WPU

Life at MIT World Peace University goes beyond academics. Students enjoy a balanced lifestyle with a mix of cultural, technical, and sports events.

Clubs and activities include:

Coding and robotics clubs

Debate and drama societies

Dance and music groups

Photography and media clubs

Entrepreneurship and innovation cell

Annual fests like Aarohan, TEDx, and Peace Talks

The university promotes mental and emotional wellness along with career development.

Career Scope After Studying at MIT World Peace University

Students who graduate from MIT World Peace University have a wide range of career options:

Placement in top companies across India and abroad

Higher studies like M.Tech, MBA, MS in international universities

Start their own businesses or startups

Work in research and development

Appear for government exams and public services

The university provides career guidance and alumni support to help students make the right choices.

Final Words

MIT World Peace University is more than just a university — it’s a learning experience that shapes your future in every way. With its strong academic foundation, focus on values and peace, and commitment to student success, it is the ideal place to build a bright career.

If you are serious about your future and want to study in a peaceful, global, and innovation-driven environment, then MIT World Peace University is the place to be.

If you need further information contact:

523, 5th Floor, Wave Silver Tower, Sec-18 Noida, UP-201301

+91 9711016766

infocollegedunias@gmail.com

[despuneuniversityblogs]

B.Tech in Electronics and Communication Engineering: A Comprehensive Guide for Aspiring Engineers

Are you passionate about technology, communication systems, and electronics? A Bachelor of Technology (B.Tech) in Electronics and Communication Engineering (ECE) offers a dynamic and future-ready career path. This program integrates core principles of electronics with modern communication technologies, preparing students for diverse roles in today's tech-driven world.

Understanding Electronics and Communication Engineering

Electronics and Communication Engineering is a discipline that combines electronic engineering with computer science and information technology. It focuses on designing, developing, and testing electronic circuits, devices, and communication equipment like transmitters, receivers, and integrated circuits. This field is pivotal in the advancement of technologies such as mobile phones, satellite systems, and the Internet of Things (IoT).

Course Structure and Curriculum

The B.Tech ECE program typically spans four years, divided into eight semesters. The curriculum is designed to provide a strong foundation in both theoretical and practical aspects of electronics and communication.

Core Subjects:

Digital Electronics

Analog Circuits

Signals and Systems

Electromagnetic Field Theory

Microprocessors and Microcontrollers

Communication Systems

VLSI Design

Embedded Systems

Wireless Communication

Optical Communication

Laboratory Work:

Hands-on experience is a crucial part of the program, with labs focusing on circuit design, signal processing, microprocessor programming, and communication systems.

Electives and Specializations:

Students can choose electives in areas like:

Artificial Intelligence and Machine Learning

Internet of Things (IoT)

Robotics

Nanotechnology

Biomedical Engineering

Eligibility and Admission Process

To enroll in a B.Tech ECE program, candidates must meet the following criteria:

Educational Qualification: Completion of 10+2 with Physics, Chemistry, and Mathematics as core subjects.

Minimum Marks: A minimum aggregate score of 50-60% in the qualifying examination (may vary by institution).

Entrance Exams: Qualifying scores in entrance exams like JEE Main, state-level CETs, or institution-specific tests.

Career Opportunities After B.Tech ECE

Graduates of ECE have a plethora of career options across various industries.

Job Roles:

Electronics Engineer

Communication Engineer

Embedded Systems Developer

Network Engineer

VLSI Design Engineer

IoT Developer

RF Engineer

R&D Engineer

Industries:

Telecommunications

Consumer Electronics

Automotive

Aerospace

Healthcare Technology

Defense and Military

Information Technology

Higher Studies:

Graduates can pursue M.Tech, MBA, or research programs in specialized fields to enhance their knowledge and career prospects.

Top Electronics and Communication Engineering Colleges in Pune

Pune is home to several esteemed institutions offering B.Tech in ECE:

DES Pune University

MIT World Peace University (MIT-WPU)

Vishwakarma Institute of Information Technology

Dr. D. Y. Patil Institute of Technology

Bharati Vidyapeeth Deemed University College of Engineering

PES Modern College of Engineering

These colleges are known for their robust curriculum, experienced faculty, and excellent placement records.

Why Choose DES Pune University for B.Tech ECE?

At DES Pune University, the B.Tech in Electronics and Communication Engineering program is meticulously designed to align with industry standards and technological advancements. The university offers:

Comprehensive Curriculum: Integrating core ECE subjects with emerging technologies.

State-of-the-Art Laboratories: Equipped with modern tools and equipment for practical learning.

Experienced Faculty: A team of dedicated educators and industry professionals.

Industry Collaborations: Partnerships with leading companies for internships and projects.

Placement Support: Dedicated cell to assist students in securing employment opportunities.

Choosing DES Pune University ensures a holistic education experience, preparing students to excel in the ever-evolving field of electronics and communication engineering.

Embark on a journey of innovation and technology with a B.Tech in Electronics and Communication Engineering. Equip yourself with the skills and knowledge to shape the future of communication and electronic systems.

[jcmarchi]

Interactive mouthpiece opens new opportunities for health data, assistive technology, and hands-free interactions

New Post has been published on https://thedigitalinsider.com/interactive-mouthpiece-opens-new-opportunities-for-health-data-assistive-technology-and-hands-free-interactions/

Interactive mouthpiece opens new opportunities for health data, assistive technology, and hands-free interactions

When you think about hands-free devices, you might picture Alexa and other voice-activated in-home assistants, Bluetooth earpieces, or asking Siri to make a phone call in your car. You might not imagine using your mouth to communicate with other devices like a computer or a phone remotely. 

Thinking outside the box, MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) and Aarhus University researchers have now engineered “MouthIO,” a dental brace that can be fabricated with sensors and feedback components to capture in-mouth interactions and data. This interactive wearable could eventually assist dentists and other doctors with collecting health data and help motor-impaired individuals interact with a phone, computer, or fitness tracker using their mouths.

Resembling an electronic retainer, MouthIO is a see-through brace that fits the specifications of your upper or lower set of teeth from a scan. The researchers created a plugin for the modeling software Blender to help users tailor the device to fit a dental scan, where you can then 3D print your design in dental resin. This computer-aided design tool allows users to digitally customize a panel (called PCB housing) on the side to integrate electronic components like batteries, sensors (including detectors for temperature and acceleration, as well as tongue-touch sensors), and actuators (like vibration motors and LEDs for feedback). You can also place small electronics outside of the PCB housing on individual teeth.

Play video

MouthIO: Fabricating Customizable Oral User Interfaces with Integrated Sensing and Actuation Video: MIT CSAIL

The active mouth

“The mouth is a really interesting place for an interactive wearable and can open up many opportunities, but has remained largely unexplored due to its complexity,” says senior author Michael Wessely, a former CSAIL postdoc and senior author on a paper about MouthIO who is now an assistant professor at Aarhus University. “This compact, humid environment has elaborate geometries, making it hard to build a wearable interface to place inside. With MouthIO, though, we’ve developed a new kind of device that’s comfortable, safe, and almost invisible to others. Dentists and other doctors are eager about MouthIO for its potential to provide new health insights, tracking things like teeth grinding and potentially bacteria in your saliva.”

The excitement for MouthIO’s potential in health monitoring stems from initial experiments. The team found that their device could track bruxism (the habit of grinding teeth) by embedding an accelerometer within the brace to track jaw movements. When attached to the lower set of teeth, MouthIO detected when users grind and bite, with the data charted to show how often users did each.

Wessely and his colleagues’ customizable brace could one day help users with motor impairments, too. The team connected small touchpads to MouthIO, helping detect when a user’s tongue taps their teeth. These interactions could be sent via Bluetooth to scroll across a webpage, for example, allowing the tongue to act as a “third hand” to open up a new avenue for hands-free interaction.

“MouthIO is a great example how miniature electronics now allow us to integrate sensing into a broad range of everyday interactions,” says study co-author Stefanie Mueller, the TIBCO Career Development Associate Professor in the MIT departments of Electrical Engineering and Computer Science and Mechanical Engineering and leader of the HCI Engineering Group at CSAIL. “I’m especially excited about the potential to help improve accessibility and track potential health issues among users.”

Molding and making MouthIO

To get a 3D model of your teeth, you can first create a physical impression and fill it with plaster. You can then scan your mold with a mobile app like Polycam and upload that to Blender. Using the researchers’ plugin within this program, you can clean up your dental scan to outline a precise brace design. Finally, you 3D print your digital creation in clear dental resin, where the electronic components can then be soldered on. Users can create a standard brace that covers their teeth, or opt for an “open-bite” design within their Blender plugin. The latter fits more like open-finger gloves, exposing the tips of your teeth, which helps users avoid lisping and talk naturally.

This “do it yourself” method costs roughly $15 to produce and takes two hours to be 3D-printed. MouthIO can also be fabricated with a more expensive, professional-level teeth scanner similar to what dentists and orthodontists use, which is faster and less labor-intensive.

Compared to its closed counterpart, which fully covers your teeth, the researchers view the open-bite design as a more comfortable option. The team preferred to use it for beverage monitoring experiments, where they fabricated a brace capable of alerting users when a drink was too hot. This iteration of MouthIO had a temperature sensor and a monitor embedded within the PCB housing that vibrated when a drink exceeded 65 degrees Celsius (or 149 degrees Fahrenheit). This could help individuals with mouth numbness better understand what they’re consuming.

In a user study, participants also preferred the open-bite version of MouthIO. “We found that our device could be suitable for everyday use in the future,” says study lead author and Aarhus University PhD student Yijing Jiang. “Since the tongue can touch the front teeth in our open-bite design, users don’t have a lisp. This made users feel more comfortable wearing the device during extended periods with breaks, similar to how people use retainers.”

The team’s initial findings indicate that MouthIO is a cost-effective, accessible, and customizable interface, and the team is working on a more long-term study to evaluate its viability further. They’re looking to improve its design, including experimenting with more flexible materials, and placing it in other parts of the mouth, like the cheek and the palate. Among these ideas, the researchers have already prototyped two new designs for MouthIO: a single-sided brace for even higher comfort when wearing MouthIO while also being fully invisible to others, and another fully capable of wireless charging and communication.

Jiang, Mueller, and Wessely’s co-authors include PhD student Julia Kleinau, master’s student Till Max Eckroth, and associate professor Eve Hoggan, all of Aarhus University. Their work was supported by a Novo Nordisk Foundation grant and was presented at ACM’s Symposium on User Interface Software and Technology.

[cleverhottubmiracle]

[ad_1] What would a behind-the-scenes look at a video generated by an artificial intelligence model be like? You might think the process is similar to stop-motion animation, where many images are created and stitched together, but that’s not quite the case for “diffusion models” like OpenAl's SORA and Google's VEO 2.Instead of producing a video frame-by-frame (or “autoregressively”), these systems process the entire sequence at once. The resulting clip is often photorealistic, but the process is slow and doesn’t allow for on-the-fly changes. Scientists from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Adobe Research have now developed a hybrid approach, called “CausVid,” to create videos in seconds. Much like a quick-witted student learning from a well-versed teacher, a full-sequence diffusion model trains an autoregressive system to swiftly predict the next frame while ensuring high quality and consistency. CausVid’s student model can then generate clips from a simple text prompt, turning a photo into a moving scene, extending a video, or altering its creations with new inputs mid-generation.This dynamic tool enables fast, interactive content creation, cutting a 50-step process into just a few actions. It can craft many imaginative and artistic scenes, such as a paper airplane morphing into a swan, woolly mammoths venturing through snow, or a child jumping in a puddle. Users can also make an initial prompt, like “generate a man crossing the street,” and then make follow-up inputs to add new elements to the scene, like “he writes in his notebook when he gets to the opposite sidewalk.” A video produced by CausVid illustrates its ability to create smooth, high-quality content. AI-generated animation courtesy of the researchers. The CSAIL researchers say that the model could be used for different video editing tasks, like helping viewers understand a livestream in a different language by generating a video that syncs with an audio translation. It could also help render new content in a video game or quickly produce training simulations to teach robots new tasks.Tianwei Yin SM ’25, PhD ’25, a recently graduated student in electrical engineering and computer science and CSAIL affiliate, attributes the model’s strength to its mixed approach.“CausVid combines a pre-trained diffusion-based model with autoregressive architecture that’s typically found in text generation models,” says Yin, co-lead author of a new paper about the tool. “This AI-powered teacher model can envision future steps to train a frame-by-frame system to avoid making rendering errors.”Yin’s co-lead author, Qiang Zhang, is a research scientist at xAI and a former CSAIL visiting researcher. They worked on the project with Adobe Research scientists Richard Zhang, Eli Shechtman, and Xun Huang, and two CSAIL principal investigators: MIT professors Bill Freeman and Frédo Durand.Caus(Vid) and effectMany autoregressive models can create a video that’s initially smooth, but the quality tends to drop off later in the sequence. A clip of a person running might seem lifelike at first, but their legs begin to flail in unnatural directions, indicating frame-to-frame inconsistencies (also called “error accumulation”).Error-prone video generation was common in prior causal approaches, which learned to predict frames one by one on their own. CausVid instead uses a high-powered diffusion model to teach a simpler system its general video expertise, enabling it to create smooth visuals, but much faster. Play video CausVid enables fast, interactive video creation, cutting a 50-step process into just a few actions. Video courtesy of the researchers. CausVid displayed its video-making aptitude when researchers tested its ability to make high-resolution, 10-second-long videos. It outperformed baselines like “OpenSORA” and “MovieGen,” working up to 100 times faster than its competition while producing the most stable, high-quality clips.Then, Yin and his colleagues tested CausVid’s ability to put out stable 30-second videos, where it also topped comparable models on quality and consistency. These results indicate that CausVid may eventually produce stable, hours-long videos, or even an indefinite duration.A subsequent study revealed that users preferred the videos generated by CausVid’s student model over its diffusion-based teacher.“The speed of the autoregressive model really makes a difference,” says Yin. “Its videos look just as good as the teacher’s ones, but with less time to produce, the trade-off is that its visuals are less diverse.”CausVid also excelled when tested on over 900 prompts using a text-to-video dataset, receiving the top overall score of 84.27. It boasted the best metrics in categories like imaging quality and realistic human actions, eclipsing state-of-the-art video generation models like “Vchitect” and “Gen-3.”While an efficient step forward in AI video generation, CausVid may soon be able to design visuals even faster — perhaps instantly — with a smaller causal architecture. Yin says that if the model is trained on domain-specific datasets, it will likely create higher-quality clips for robotics and gaming.Experts say that this hybrid system is a promising upgrade from diffusion models, which are currently bogged down by processing speeds. “[Diffusion models] are way slower than LLMs [large language models] or generative image models,” says Carnegie Mellon University Assistant Professor Jun-Yan Zhu, who was not involved in the paper. “This new work changes that, making video generation much more efficient. That means better streaming speed, more interactive applications, and lower carbon footprints.”The team’s work was supported, in part, by the Amazon Science Hub, the Gwangju Institute of Science and Technology, Adobe, Google, the U.S. Air Force Research Laboratory, and the U.S. Air Force Artificial Intelligence Accelerator. CausVid will be presented at the Conference on Computer Vision and Pattern Recognition in June. [ad_2] Source link

[fromdevcom]

Artificial Intelligence (AI) is no longer a futuristic concept; it is the driving force behind many of today's technological advancements. As industries increasingly integrate AI, the demand for skilled professionals in this field has surged. Choosing the right university to study AI is a crucial step for anyone looking to make a mark in this dynamic domain. This article highlights the best universities worldwide that offer exceptional AI programs, providing students with the knowledge and skills needed to lead in this ever-evolving field. The Importance of AI Education AI has the potential to revolutionize various sectors, including healthcare, finance, transportation, and more. To be at the forefront of these changes, students need a strong educational foundation that combines theoretical knowledge with practical experience. Universities play a pivotal role in shaping the future of AI by offering cutting-edge research opportunities, state-of-the-art facilities, and experienced faculty who are pioneers in their respective fields. Top Universities for AI Studies 1. Massachusetts Institute of Technology (MIT) - USA MIT is renowned globally for its contributions to AI research and education. The university's Computer Science and Artificial Intelligence Laboratory (CSAIL) is one of the largest and most influential AI research labs in the world. MIT offers a wide range of AI-related courses and degrees, including specialized programs in machine learning, robotics, and natural language processing. Students at MIT benefit from a collaborative environment that fosters innovation and creativity. 2. Stanford University - USA Stanford University has been a leader in AI research for decades. The university's AI Lab, established in 1962, has played a significant role in advancing the field. Stanford offers a comprehensive curriculum that covers all aspects of AI, from foundational theories to advanced applications. Students have the opportunity to work on groundbreaking projects alongside leading experts in AI and machine learning. 3. University of California, Berkeley (UC Berkeley) - USA UC Berkeley is another top institution known for its AI programs. The university's Berkeley Artificial Intelligence Research (BAIR) Lab is at the forefront of AI innovation, with research spanning machine learning, computer vision, and robotics. UC Berkeley's AI courses are designed to provide students with a deep understanding of both the theoretical and practical aspects of AI, preparing them for careers in academia, industry, and beyond. 4. University of Oxford - UK The University of Oxford offers one of the most prestigious AI programs in Europe. The university's Department of Computer Science is home to world-leading researchers in AI and machine learning. Oxford's AI curriculum emphasizes both the technical and ethical dimensions of AI, ensuring that graduates are well-equipped to address the challenges of AI deployment in real-world scenarios. 5. Carnegie Mellon University (CMU) - USA Carnegie Mellon University is widely recognized for its AI research and education. The university's School of Computer Science offers a variety of AI-related programs, including specialized degrees in machine learning, robotics, and language technologies. CMU's strong industry connections provide students with numerous opportunities for internships, collaborations, and job placements in leading tech companies. Emerging Leaders in AI Education While the aforementioned universities have long been established as leaders in AI education, several institutions are rapidly gaining recognition for their contributions to the field: ETH Zurich - Switzerland: Known for its rigorous academic programs, ETH Zurich is becoming a hub for AI research in Europe, particularly in robotics and autonomous systems. Tsinghua University - China: Tsinghua University has emerged as a leading institution for AI research in Asia, with a focus on AI applications in smart cities, healthcare, and more.

National University of Singapore (NUS) - Singapore: NUS is gaining international recognition for its AI programs, particularly in areas such as natural language processing and machine learning. Conclusion Choosing the right university for AI studies is a critical decision that can shape your future career. The universities highlighted in this article are at the forefront of AI research and education, offering students unparalleled opportunities to learn from the best in the field. Whether you're looking to pursue a career in academia, industry, or entrepreneurship, these institutions provide the resources and environment needed to succeed in the ever-evolving world of AI.