The event showcased urgency for formal recognition of Hinduphobia via initiatives like H.Res 1131

WASHINGTON, June 28, 2024 /PRNewswire/ -- Lawmakers, Hindu students, researchers, and community leaders came together in a packed room during the 3rd National Hindu Advocacy Day on the Hill, to discuss the concerns Hindus living in the US face. Close to 25 lawmakers (a mix of congressional representatives and staffers both Democrat and Republican) attended the event, organized by the Coalition of Hindus of North America (CoHNA) which highlighted the multi-pronged attacks Hindus face. These range from the continued usage of stereotypical colonial frameworks, to gaslighting and verbal slurs, and all the way to the vandalizations of multiple temples. Over 100 delegates (including a large number of Hindu youth) from 15 states attended the event and 40 plus core CoHNA volunteers visited over 115 congressional offices to advocate support for H.Res.1131, which condemns Hinduphobia and attacks on temples, while celebrating the contribution of the Hindu American community. Watch vignettes from the day here.

"From students to retired community members of diverse backgrounds, CoHNA's Advocacy Day has grown steadily to become an important mechanism through which our community engages with lawmakers on the Hill," remarked CoHNA President Nikunj Trivedi. "We are also glad to see other organizations as well as non-Hindu allies join us in support of the causes that matter to our community and especially our youth."

The highlight of the event was the multiplicity of student voices. Attendees heard heartfelt personal testimony from a powerful panel of Hindu students from Stanford, UC Berkeley, and University of Georgia. They delved into the challenges they face on campus, in academic settings, and even in their dorm rooms. Their voices and stories brought home the prevalent Hinduphobia on campus and the way it shapes their lives and the choices they make.

Rutvij Holay spoke of being mocked for having a small space for Hindu worship in his dorm room and of having to console a close Kashmiri friend who was traumatized by the display of on-campus displays sanitizing the ethnic cleansing his community had faced. Aryan Sawant shared his isolation in being an openly proud Hindu on campus and having to deal with the disapproval of peers. He highlighted the misinformation by professors who deny anti-Hindu hate, even as they peddle it by denying the religious nature of recorded pogroms against Hindus around the world such as the 1971 Bengali Hindu Genocide. Anvita Yerramsetty shared how growing awareness of anti-Hindu hate in her high school years strengthened her resolve to stay proud of her roots and reshaped her decision and research on something as fundamental as where to apply and go to college.

Surya Naga, the Youth Director for Hindu on Campus, presented data collected from student testimonials across the United States and the impact of such experiences on a student's psyche - from students being told to wipe off the bindis on their foreheads and attempts to rip of their sacred threads, to being made fun of for worshiping Hindu deities with "weird names," to being accused of supporting extremism and oppression of minorities just because of one's Hindu identity, etc.

American Hindus have just lived through a turbulent year and these issues were highlighted throughout the event. Data shows a rise in hate against Hindus. Academic Hinduphobia has been amplified as a result of the turmoil on college campuses and Hindu students shared personal stories of the many ways they get targeted on campus. And even sacred spaces are not safe -- SIX Hindu temples were attacked in California between Nov. 2023-Jan. 2024, with no resulting action and little lasting outrage. A detailed list of the incidents waspublished in April.

Congressional Support

The event began with Congressman Max Miller (R-OH), talking about the importance of freedom of religion and sharing how proud he was for supporting H.Res 1131. He expressed empathy with the issues the Hindu community has been facing, and assured that he would continue to stand against all forms of hate and bigotry throughout the country. He acknowledged that it was a tough time for the country, but that he would be there for the Hindu community: "If anything were to happen to your community, I'll be there standing shoulder to shoulder with you." He also asked the audience to stand strong and never back away from their values.

CoHNA was excited to host the force behind H.Res 1131 - Congressman Shri Thanedar (D-MI) - who stressed he will not tolerate Hinduphobia, discrimination, or other forms of hate. "We are here and we are fighting," he said, drawing attention to "the voice you all have, the voice the Hindu community has in Congress." Thanedar spoke of why H.Res. 1131 was needed in the first place and also shared his own immigration story as a way of illustrating the great American story and the ability to surmount hurdles.

Sharing his excitement at being back at CoHNA's event, Congressman Rich McCormick (R-GA) welcomed the continued and growing engagement of the Hindu American and Indian American community in policy making and its potential to transform the future of America. He called attention to his support for H.Res 1131, honoring the contributions of Hindu Americans, and asked the community to continue pursuing the American dream which celebrates innovation, hard work, success, AND its traditions.

Other lawmakers like Congressman Glen Grothman (R-WI) also expressed solidarity with the community and congratulated CoHNA for being a force in advocating for the community

Closing out the day, Congressman Ro Khanna (D-CA) celebrated the growth of the community's advocacy over the past decade, and lauded CoHNA's efforts in ensuring the community has a growing voice on Capitol Hill via advocacy events. He exhorted everyone to be proud of who they are and congratulated the audience on making time to come to DC for an event that exemplified pride in their heritage and roots.

Several lawmakers also spoke about the importance of tackling immigration - especially problems like the Green Card backlog - an issue that has an outsized impact on the Hindu American immigrant community.

In addition to lawmakers and staffers, the event was also attended by community leaders and representatives from various organizations such as HinduACTion, Howard County Jewish Advocacy Group (HoCoJAG), ISKCON, Association of United Hindu and Jain Temples, Americans for Hindus (A4H), Indian Cultural Association of Howard County, etc.

Data and Research

Aaron Gross, Research Fellow at Network Contagion Research Institute (NCRI), highlighted the alarming rise of Hinduphobia in North America, driven by the Khalistan extremist movement and attacks on temples, along with the need for law enforcement to tackle online hate before it escalates into further violence. NCRI's analysis of online chatter surrounding real life anti-Hindu hate incidents (attacks on temples, vandalization of Gandhi statues, etc.) pointed to the involvement of Khalistan movement supporters, a group advocating for the creation of a separate Sikh nation out of Punjab, India. Each attack was preceded and followed by a spike in online posts promoting violence, powered by a bot network designed to amplify anti-Hindu sentiment. Often, these posts include videos from Gurpatwant Singh Pannun, leader of Sikhs for Justice, who openly incites his followers to target Hindus in Canada, US, and India. Interestingly, about 20% of these Twitter accounts purport to be from Pakistan, where Sikhs constitute less than 0.02% of the population. This suggests that many of these accounts do not genuinely support Sikh separatism but are driven by Hinduphobia and geo political considerations.

Rana Reddy, CoHNA's Policy Fellow, shared his analysis of a report recently published by Carnegie Mellon University. He showed how geo-political players use Hinduism to target India even though India is a secular country. And in a digital world, these anti-India tropes are used to target Hindus across the globe. The key report findings - organized cybercrime, bot networks, and sophisticated disinformation tactics to propagate Hinduphobia globally by exploiting/misrepresenting Indian political narratives for targeted information attacks. He concluded that counter strategies and reporting mechanisms are required by private distribution platforms to mitigate this digital threat through robust cybersecurity measures and international regulatory bodies.

About CoHNA

CoHNA is a grassroots level advocacy and civil rights organization dedicated to improving the understanding of Hinduism in North America by working on matters related to the Hindu community and by educating the public about Hindu heritage and tradition. For more information, please visithttps://cohna.org or follow us onTwitter,Facebook,LinkedIn and onInstagram.

SOURCE Coalition of Hindus of North America

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Testimony on Persistent Targeting of American Hindu Students and Attacks on Hindu Temples Resonate at CoHNA's ... - PR Newswire

In a recent study published in Physical Review Letters, Professor Wei Guo from Florida State Universityprovided valuable insights into the quantum states of electrons on qubits.

Quantum computers have the potential to revolutionize technology by performing calculations that would take classical computers many years to complete.

To build an effective quantum computer, a reliable quantum bit, or qubit, is essential. A qubit must be able to exist simultaneously in both the 0 and 1 states for a sufficiently long period, known as its coherence time.

One promising approach involves trapping a single electron on a solid neon surface, creating what is known as an electron-on-solid-neon qubit.

Guos team discovered that small bumps on the surface of solid neon can naturally bind electrons, forming ring-shaped quantum states. These quantum states describe various properties of an electron, such as position, momentum, and other characteristics before measurement. When these bumps are of a certain size, the electrons transition energythe energy required for an electron to move from one quantum ring state to anotheraligns with the energy of microwave photons, another type of elementary particle.

This alignment allows for the controlled manipulation of electrons, which is crucial for quantum computing.

This work significantly advances our understanding of the electron-trapping mechanism on a promising quantum computing platform, it not only clarifies puzzling experimental observations but also delivers crucial insights for the design, optimization, and control of electron-on-solid-neon qubits.

Wei Guo, Professor, Florida State University

Guo and collaborators previously demonstrated the feasibility of a solid-state single-electron qubit platform using electrons trapped on solid neon. Recent research has revealed coherence times of up to 0.1 milliseconds100 times longer than the typical 1 microsecond coherence time for conventional semiconductor-based and superconductor-based charge qubits.

The extended coherence time of the electron-on-solid-neon qubit is attributed to the inertness and purity of solid neon. This system also addresses the issue of liquid surface vibrations, a problem inherent in the more extensively studied electron-on-liquid-helium qubit. The current research provides crucial insights into further optimizing the electron-on-solid-neon qubit.

A key aspect of this optimization involves creating qubits that are smooth across most of the solid neon surface while having bumps of the right size where needed. Designers aim to minimize naturally occurring surface bumps that attract disruptive background electrical charge. Simultaneously, intentionally fabricating bumps of the correct size within the microwave resonator on the qubit enhances its ability to trap electrons effectively.

This research underscores the critical need for further study of how different conditions affect neon qubit manufacturing, Neon injection temperatures, and pressure influence the final qubit product. The more control we have over this process, the more precise we can build, and the closer we move to quantum computing that can solve currently unmanageable calculations.

Wei Guo, Professor, Florida State University

Toshiaki Kanai, a Graduate Research Student in the FSU Department of Physics, and Dafei Jin, an Associate Professor at the University of Notre Dame are the Co-authors of the study.

The National Science Foundation, the Gordon and Betty Moore Foundation, and the Air Force Office of Scientific Research supported the research.

Kanai, T., et al. (2024) Single-Electron Qubits Based on Quantum Ring States on Solid Neon Surface. Physical Review Letters. doi.org/10.1103/PhysRevLett.132.250603.

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Study Reveals Insights into Electron-on-Solid-Neon Qubits for Quantum Computing - AZoQuantum

Insider Brief

PRESS RELEASE Foresight Group (Foresight), the leading listed infrastructure and regional private equity investment manager, has led a 2.2 million growth capital investment into Cavero Quantum Ltd (Cavero Quantum or the Company) alongside co-investor, Northern Gritstone.

Cavero Quantum, a University of Leeds spinout, has developed a new passwordless encryption technology for secure key generation and authentication. It is compatible with legacy hardware, requires little bandwidth and has the potential to be potentially secure against cyber attacks by quantum computers.

The technology is attractive to a wide range of sectors and has immediate market application through replacing multi-factor authentication and one-time passwords with a high security, frictionless, passwordless form of authentication.

Founded by Professor Ben Varcoe and Dr Frey Wilson, Cavero Quantum will use the funding to begin commercialising its technology and launch its first product. Ben will support Cavero Quantum alongside his existing role as Professor of Quantum Information Science at the University of Leeds, while Frey will become Chief Technology Officer.

As part of the investment, the founders will be supported by the appointment of James Trenholme, as CEO, and Andrew Wallace as Chair. James is an experienced software entrepreneur who has previously founded and exited an identity services start-up, whilst Andrew Wallace has significant deep-tech experience in quantum computing.

Foresight has invested alongside Northern Gritstone, an investment company dedicated to supporting ambitious science and technology-enabled businesses in the North of England, including through its venture-building program NG Studios powered by Deeptech Labs, in which Cavero Quantum participated earlier this year.

Cyber attacks are estimated to cost the global economy $7 trillion per year and are driving investment across the cyber security market, including in passwordless authentication which is projected to be worth 17 billion per year by 2027. Demand for Caveros solution is expected to further increase as existing cryptographic methods become more vulnerable to quantum computers.

Richard Ralph, Investment Manager at Foresight, said: Whilst Cavero Quantums technology is potentially revolutionary to quantum cryptography, it offers the potential for immediate improvements on existing cryptographic approaches due to its dual authentication and passwordless nature, thereby providing improved security against existing cyber attacks. The technology has been independently validated and we look forward to working with Ben, Frey, James, Andrew and Northern Gritstone to commercialise this innovative technology.

James Trenholme, CEO at Cavero Quantum, commented: The technologythat Ben, Frey and the experimental quantum science team at the University of Leeds have built reallyisground-breakingtechnology.Itsthe first solution in the world that can replace security standards like ECDH without compromising on architecture and customer experience, keeping data safe for the future as Quantum computing becomes the norm. Its an honour to lead Cavero Quantum. This is a great team, and Im looking forward to building a great business together.

Duncan Johnson, Chief Executive Officer at Northern Gritstone, added: Cavero Quantums technology is applicable today and has the potential to allow individuals, businesses and nations to function safely in a post-quantum world. Spun out of the University of Leeds innovation ecosystem, one of Northern Gritstones university partners, Cavero Quantum is an example of a world-class business of tomorrow built on the amazing science and technology that exists in the North of England today.

Professor Nick Plant, Deputy Vice-Chancellor: Research and Innovation, University of Leeds, said: It is inspiring to see how the experimental quantum science team at Leeds has developed solutions for such a critical issue in online security. Caveros technology will have a major impact on our global community, making sector-leading improvements and bringing financial savings to businesses. It is testament to the world-leading, innovative technology being driven by our region.

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Foresight Leads 2.2 Million Growth Capital Investment Into Cavero Quantum - The Quantum Insider

Insider Brief

A team of scientists said an innovative ensemble deep learning model combined with quantum machine learning classifiers might improve the accuracy and efficiency of Alzheimers disease (AD) classification, according to a study published in Nature.

The researchers, from the University of Gondar in Ethiopia, used the classifiers to investigate Alzheimers disease, a chronic neurodegenerative disorder. Early diagnosis is crucial for timely intervention and treatment, potentially improving the quality of life for those affected. Traditional methods for diagnosing Alzheimers have limitations in accuracy and efficiency, prompting researchers to explore advanced technologies, such as quantum computing.

Quantum Computing and Deep Learning

Quantum computing offers a promising alternative to classical machine learning approaches for various disease classification tasks. Quantum computers, while still under development, can theoretically process complex data and perform calculations at a much faster rate, leveraging quantums unique potential to handle large datasets more efficiently and accurately.

The team leveraged this potential by developing a model that integrates deep learning architectures and quantum machine learning algorithms. This hybrid approach aims to enhance the precision and speed of Alzheimers diagnosis.

The study used data from the Alzheimers Disease Neuroimaging Initiative I (ADNI1) and Alzheimers Disease Neuroimaging Initiative II (ADNI2) datasets. These datasets, comprising MRI brain images, were merged and pre-processed to form the basis of the proposed model. Key features were extracted using a customized version of VGG16 and ResNet50 models. These features were then fed into a Quantum Support Vector Machine (QSVM) classifier to categorize the data into four stages: non-demented, very mild demented, mild demented, and moderate demented.

The ensemble deep learning model combined the strengths of both VGG16 and ResNet50 architectures, deep learning architectures used for image recognition tasks. VGG16 is known for its simplicity and deep convolutional layers, while ResNet50 introduces residual connections to allow for training of very deep networks without performance degradation. The QSVM classifier provided the computational power of quantum algorithms. This combination aimed to enhance the overall performance of the classification model.

Evaluation and Results

The performance of the proposed model was evaluated using six metrics: accuracy, area under the curve (AUC), F1-score, precision and recall. The results demonstrated that the ensemble model significantly outperformed several state-of-the-art methods in detecting Alzheimers disease.

These results lean toward the superiority of the ensemble model with QSVM in accurately classifying AD stages from the merged ADNI dataset. Its important to note that the ResNet + QSVM model exhibited a 6% improvement in accuracy compared to the standalone ResNet model, while the proposed ensemble model showed 8.5% and 12.21% better results compared to other ensemble and SVM models, respectively.

The experiments were conducted using a Hewlett Packard Core i5, sixth-generation computer with 8 GB RAM, and a Google Colab Pro GPU.On the quantum side, the researchers relied on a 5-qubit quantum hardware or simulator, employing the QSVM model from the Qiskit library. This setup allowed for efficient processing and analysis of the MRI brain images, demonstrating the practical application of quantum computing in medical research.

Implications and Future Research

The study highlights the potential of combining quantum classifiers and ensemble learning to achieve effective outcomes in disease classification tasks. The integration of quantum machine learning classifiers with deep learning architectures can significantly improve the accuracy and efficiency of Alzheimers disease diagnosis.

However, the researchers acknowledge the need for further studies to evaluate the practical implementation of this model within medical devices. Future research could focus on integrating the proposed model into real-world medical settings, providing a significant solution to support primary care for Alzheimers disease, especially in cases where MRI scans are blurred or challenging to interpret.

The researchers include: researchers Abebech Jenber Belay, Yelkal Mulualem and elaku Bitew Haile, all of the department of Information Technology, College of Informatics, University of Gondar, Gondar, Ethiopia.

Link:

University of Gondar Scientists Say Quantum Computers Offer Promising Boost to Alzheimer's Diagnosis - The Quantum Insider

International Day of Yoga is celebrated worldwide on June 21. In 2015, when this was first commemorated, some 36,000 enthusiasts including the Indian prime minister, Narendra Modi, and dignitaries from 84 countries lined up in New Delhi, for the worlds largest yoga session.

Sessions were also held on the bank of the River Thames in London and under the Eiffel Tower in Paris. Last year, Modi led a yoga session at the UN headquarters in New York. Also last year, the Indian city of Surat hosted the worlds largest yoga session, with over 150,000 participants.

Yoga has thoroughly permeated global consumer culture and everyday news ranges from the glamorous to the absurd. The Louvre has announced yoga classes for visitors to coincide with the Olympics in Paris in June. Italy recently banned puppy yoga, saying only adult dogs could participate, for reasons of animal welfare.

UNIVERSAL APPEAL

According to one estimate, some 300 million people practise yoga worldwide. Yoga has also made significant inroads in Pakistan over the last decade. A quick search in major cities reveals an abundance of programmes and studios.

The ancient practice of yoga is a worldwide phenomenon due to its many touted mental and physical health benefits. But do these claims stand up to scientific scrutiny?

Many of these options are backed up with glossy Instagram feeds of models, twisting their bodies into the trademark poses, once so fantastical but now entirely familiar. In May, Islamabads Capital Development Authority launched complimentary classes for residents in the F-9 Park.

But beyond the glamour and buzz, the average person has questions: what is all this hype about? How is yoga different

from other fitness routines? Is it actually something special?

FROM THE SCIENTIFIC LENS

Some of yogas scientifically documented benefits are only to be expected: studies show that yoga significantly improves flexibility; it helps combat arthritis; yoga is effective against carpal tunnel syndrome; it alleviates chronic lower back pain; and it seems to be a promising aid in weight loss.

Yoga has a pronounced meditation component, and studies show significant stress reduction, which can have cascading effects on reducing risk of heart attacks, strokes, chronic disease, etc.

But when one starts to delve deeper, things get interesting fast.

Consider an early and intriguing study from Duke University, which compared health benefits of yoga with aerobics for almost a hundred adults.

At the time of the study, in 1989, the magical secret to fitness was to increase ones maximal oxygen uptake, the VO2 max, ie the maximum volume of oxygen consumed during rigorous exercise. Decades of science and research demonstrated that aerobic exercise did precisely that, making it the dominant fitness paradigm of the era. The study results were also very clear: over the four-month study period, subjects participating in aerobics raised their VO2 max significantly. There was no increase for the yogis at all.

However, when researchers surveyed participants quality of life, the response was overwhelmingly positive for both groups. At the end of the study, yogis also felt healthier, they reported higher energy levels, endurance, flexibility and better sleep. Their social lives improved markedly. Memory and concentration were enhanced. They had less loneliness, improved self-confidence and life satisfaction. They even felt that they looked better.

THE FOUNTAIN OF YOUTH?

The literature on yoga abounds with counterintuitive findings like these. Another fascinating study from 2008 confronts the popular claim that yoga is restorative and anti-ageing. Could yoga really play a role in human longevity?

Biological ageing is linked to telomeres, which are DNA strands at the very tips of chromosomes. Every time a cell divides, these tips get shorter, making them a kind of clock, indicating the cells lifespan. This discovery an alternative way of counting biological age was significant enough to secure the Nobel Prize.

In their study, researchers investigated a group of 30 men with low-risk cancer and introduced comprehensive lifestyle changes for them, including a low-fat diet, a walking routine, and yoga-based stretching, breathing and meditation.

After three months, they reported substantial health improvements, including decreased blood pressure, cholesterol, body mass index, etc. The researchers also discovered that telomerase activity the enzyme that counteracts the shortening of telomeres increased by 30 percent.

A follow-up study five years later, featuring 10 of the same subjects, confirmed significant increases in telomere length.

The authors noted the potential of these findings for cellular longevity, tissue renewal, disease prevention, and increases in life span. Even in the understated language of science, this is bold new fountain-of-youth territory.

AN AURA OF SPIRITUALITY

Yoga has always had this mystique, a touch of the exotic and the supernatural.

In 1965, B.K.S. Iyengar the man who did more than any other to popularise yoga in the West wrote in his seminal book, Light on Yoga, how this practice can bring one to the crossroads of his destiny.

I remember coming across an old book, in a library overseas, with the intriguing title Christian Yoga. Written in the sixties by a French priest, J.M. Dechanet, the book was an intimate and inspiring memoir of his experiment to reconcile yoga with the Christian tradition.

Early in the book, he notes that reading the Bible made the contemplative lives of prophets seem distant from our noisy modern existence. Later, he realises that practising yoga, surprisingly, allowed him to experience, to an extent, the serene calm hed read about.

These are very interesting claims. We see a faint reflection of these in the science. For instance, a review paper surveying some 30 studies finds that [yoga] may be positively associated with several aspects of spirituality.

In his book, A Life Worth Breathing, author Max Strom describes a complaint that many of us will find familiar: In the morning I cant wake up, in the day I am bored, in the evening I am tired, and at night I cant sleep.

Yoga can be a wonderful antidote. Even a few weeks of practice are enough to realise that yoga facilitates a contemplative state.

Multiple surveys from different countries find that, whereas most people start yoga for its physical benefits, a large number end up maintaining the practice, primarily for its spiritual side-effects.

MORE STRENOUS THAN SPORTS

However, for those who may be motivated to jump on to a mat right away, it is important to sound a note of caution. The good news is that statistics on yoga injuries are largely reassuring: the rate is low.

A Danish study of almost 3,500 participants reported an injury prevalence of one percent for yoga. To get a sense of comparison, this figure was 38 percent for soccer players, 19 percent for runners and nine percent for those undertaking strength training. However, the bad news is that there are abundant accounts of injuries and harms.

Journalist William Broad, author of the highly recommended book The Science of Yoga, comments that [yoga] makes most other sports and exercises seem like childs play.

There are reports of students pushing their bodies beyond their limits to achieve challenging poses, resulting in torn tendons, popped ribs and blood clots. When one digs into these incidents, two main reasons pop out.

One is basic common sense: a wide-ranging survey of yoga teachers, therapists and clinicians finds that the most commonly cited culprits were [p]oor technique or alignment, previous injury, excess effort, and improper or inadequate instruction.

The second reason behind injuries is more serious and more subtle: ego. Some people tend to bring a materialist and competitive drive to yoga and rush themselves into advanced poses, out of a sense of achievement. But the pose should always be part of the journey and not the goal. It is vital to listen to the body attentively.

To quote author Max Strom again regarding yogas transformative magic: Remember, it doesnt matter how deep into a posture you go what does matter is who you are when you get there.

Like most quotes on yoga, this, too, can be maddeningly cryptic for an outsider. At the end of the day, the secret of yoga cannot really be explained. Like many of the truly good things in life, it can only be experienced.

The writer teaches at the NUST School of Electrical Engineering and Computer Science, Islamabad. He can be reached at taha.ali@gmail.com

Published in Dawn, EOS, June 23rd, 2024

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HEALTH: IS YOGA ALL ITS CRACKED UP TO BE? - DAWN.com

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A study conducted by Consumer Reports discovered that two popular brands of kids' snacks contain elevated levels of lead, though federal standards have not been set on heavy metal levels in many baby foods.

The Food and Drug Administration (FDA) has only set limits on heavy metals in infant rice cereal and juice, though it is working to put standards in place for other categories of baby foods.

The owner of Lead Safe Mama, Tamara Rubin, published a story on her website about LesserEvil and Serenity Kids products containing lead.

Rubins company focuses on preventing lead poisoning while also raising awareness for parents about sources of lead exposure. For example, she sounded the alarm on Stanley tumblers, which were found to contain lead.

More recently, Rubin found that cassava-based snacks like Serenity Kids puffs contained high levels of lead, leading Consumer Reports to test four cassava products from LesserEvil and Serenity Kids as well as two products from Once Upon a Farm that contained sorghum.

CUCUMBERS RECALLED IN 14 STATES OVER POTENTIAL SALMONELLA CONTAMINATION

Consumer Reports tested multiple types of kids' puffs and found high levels of lead in some. (Scott Meadows / Consumer Reports Website)

The study found that LesserEvils Lil Puffs Intergalactic Voyager Veggie Blend puffs contained "more lead per serving than any of the 80 baby foods" Consumer Reports has tested since 2017.

Specifically, the test found the lead content was 112% of the maximum allowable dose levels (MADLs) established by California Proposition 65.

James E. Rogers, Ph.D., head of food safety testing at Consumer Reports, said kids should consume less than half of a serving of the Intergalactic Voyager Veggie Blend puffs per day.

Consumer Reports also found LesserEvils Lil Puffs Sweet Potato Apple Asteroid and Serenity Kids Tomato & Herb, Bone Broth puffs also contained high levels of lead.

HY-VEE RECALLING MULTIPLE ITEMS, CITING SALMONELLA CONTAMINATION RISK

Consumer Reports showed in its report what an actual serving looks like for kids eating snack puffs. (Consumer Reports Website)

LesserEvils Asteroid puffs contained lead levels at 60% of the MADLs, while Serenity Kids Tomato & Herbs contained lead levels at 53%.

Based on these levels, Rogers recommended children be given 1 servings of puffs, at the most, per day.

Rogers warned that the serving sizes of the puffs are smaller than people may realize. According to Consumer Reports, a single serving of Intergalactic Voyager Veggie Blend is 17 puffs, while the Serenity Kids puffs are sold in a 1 ounce container with six servings.

The Once Upon a Farm products tested had "very low" levels of lead, Consumer Reports said, accounting for some of the lowest levels of all the baby food they have ever tested.

ALDI RECALLS CREAM CHEESE OVER SALMONELLA CONCERNS

Consumer Reports tested several kids' snacks and found some contained elevated levels of lead. (Consumer Reports Website)

"Clearly, some manufacturers need to do a better job of keeping heavy metals out of their snack foods, and there may be some particular concerns about foods made with cassava," Rogers said.

Rogers acknowledged that the FDA recently proposed limits on lead and other heavy metals in some categories of baby food. But he also noted that snack foods were not one of the categories being looked at for lead regulations.

"The agency needs to take a hard look at the snacks parents feed their children and make sure they dont have dangerous levels of lead and other contaminants," he said.

Caitlin Mack, the brand marketing director at LesserEvil, told FOX Business its products adhere to current regulatory requirements.

"LesserEvil was built on a mission to create better, cleaner, more natural products than the highly processed and refined snacks that overtook grocery store shelves for years," she said. "We are proud of the best-in-class products we've put on shelves, which all meet GRAS (Generally Recognized as Safe) standards and federal regulations for organic products. Food safety is a top priority, and we conduct extensive testing for all LesserEvil products that complies with California Prop 65 and federal standards."

Jennie Shen, director of brand marketing for Serenity Kids, told FOX Business its puffs have always been safe for consumption.

ORANGE JUICE MAKERS CONSIDER USING ALTERNATIVE FRUIT AS PRICES SKYROCKET

Cassava root and freshly made cassava flour. (Wayne Hutchinson / Farm Images / Universal Images Group / File / Getty Images)

"All of our products test well below the maximum allowable dose levels established by California Proposition 65," Shen said. "We have always addressed lead and all heavy metals head-on because we are confident in the safety of our products and ingredients, and because we believe that our products are healthier than the alternatives that exist today."

Like Consumer Reports, Shen said the FDA does not have standards and benchmarks regulating heavy metals in all baby food segments. Instead, the agency only provides drafted guidance on the matter.

Without those standards, she said Serenity Kids sought out its own standards and holds all products to the California Prop 65 exposure thresholds for heavy metals, which are some of the lowest published levels in the U.S.

"Our puffs are completely safe to consume and are compliant with applicable regulations like Prop 65 for heavy metals in the United States based on the recommended serving size," Shen said.

She also explained that heavy metals like lead are prevalent in the food system.

The manufacturers of kids' snacks say its products are below the maximum allowable dose levels of lead established by California Proposition 65. (Arturo Holmes/Getty Images for National Urban League / Getty Images)

The Serenity Kids puffs contain cassava, which Consumer Reports said has been shown through tests to contain high levels of lead. Similarly, other root vegetables like sweet potatoes, carrots and beets also contain elevated levels of lead.

Angelia Seyfferth, Ph.D., in the department of plant and soil sciences at the University of Delaware, told Consumer Reports that lead can occur naturally in soil or end up there from pollution. The lead can accumulate in a plants roots but not move very well beyond the root, she said.

Cassava can also be processed into flour and baked into snack foods, making the lead levels more concentrated.

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Shen explained that the Serenity Kids products contain whole food ingredients, so they have a state-of-the-art quality program and testing protocols. For example, they test all of their products and work with suppliers who use remediation methods to find foods with the lowest achievable levels of contaminants, then prioritize them for babies, she said.

"We also carefully vet all of our suppliers to ensure we are using the cleanest possible ingredients so that we can feel good about the safety of our foods," Shen said. "We have always addressed lead and all heavy metals head-on because we are confident in the safety of our products and ingredients, and because we believe that our products are healthier than the alternatives that exist today."

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Popular organic kids' snacks found to contain high levels of lead: Consumer Reports - Fox Business

Features Newsday Reporter Yesterday Aaron Rampersadsingh also known as Ved Valmki launched his new book, Start Meditating Today, on June 8. Photo courtesy: Gareth Leigh Photography. -

BAVINA SOOKDEO

Aaron Rampersadsingh, also known as Ved Valmki, is preaching what he practises: he's launched a book, Start Meditating Today, on June 8.

Rampersadsingh, a 36-year-old from Preysal, began yoga and meditation in his childhood, heavily influenced by his mother.

My mom was a big part of learning yoga and my spiritual journey. She got both my sister and me involved in yoga when we were children. I have been steeped in yogic philosophy and spiritual practice (since) I was five years old.

After he went to Preysal Government School and Presentation College, San Fernando, his deeper engagement with yoga blossomed during his university years at Ramapo College, New Jersey, where he studied psychology and explored the impact of yoga on consciousness.

I returned home from the US because my mom had cancer and I wanted to be with her. During that time, I delved deeper into the spiritual aspects of yoga, especially meditation.

"When she passed in 2013, I had a hard time grieving.

"I would say that yoga rescued me from that, because I went to stay at an ashram.

At the ashram (a place dedicated to yoga and spiritual living), where he spent nine months, Rampersadsinghs guru guided him to explore yoga further, leading him to teach.

A pivotal moment in his life came during a pilgrimage to India in 2015. Visiting the ancient temple of Kedarnath in the Himalayas, Rampersadsingh experienced a profound spiritual change.

Before I entered that temple, I had always felt very uncertain about my life...When I was there I felt a shift: I did have a spiritual experience there.

This experience solidified his dedication to the spiritual practice of yoga and his mission to share it with others.

My whole life has been about spiritual exploration, he said when asked about his initial goals. I never had a clear goal about what I wanted to do until after the first time I went to India. I studied psychology in university because I wanted to understand myself and people better, but I really found that in yoga.

In 2017, he returned to India after qualifying for a scholarship to SVYASA University from the Indian High Commission. There he received his yoga certification and learnt more about the science behind yogic practices.

He's been a yogacharya (yoga teacher) since 2015, working from his studio in Preysal Village since 2017. It doesn't have an official name, but is mostly referred to as the Yoga with Ved Studio.

What is most rewarding for me in teaching yoga is seeing my students and clients begin taking charge of their lives, and to see the transformative power of these ancient spiritual practices.

Inspired by his students, Rampersadsingh decided to write Start Meditating Today as a comprehensive guide to meditation.

Meditation holds so much power in it. It transcends religion and helps us to get back to the spiritual core of our being, but it is practice, a journey that requires wisdom and guidance.

Realising he could not give as much as he wanted to just by teaching meditation classes, Rampersadsingh began writing this book to share some meditation techniques and concepts.

There is so much to explore in it, but we all have to start somewhere... hence the title, Start Meditating Today."

Writing it took about a year.

Sometimes I felt like the book was writing itself...Other times I really had to stay with it, be patient, and wait for the inspiration to enter my being to continue.

The process was both a learning experience and a testament to his discipline and dedication.

The book has three parts: the basics of meditation, deeper spiritual concepts, and the integration of meditation into daily life. It aims to reach anyone interested in meditation, from beginners to those seeking to deepen their practice.

Rampersadsingh hopes readers will find practical guidance and spiritual insight.

This book is for anyone who feels attracted to meditation but does not know how to start...and certainly it is for any person, of any religion, who sincerely desires spiritual growth in their lives.

Asked why yoga is important to him, he explained he believes it is crucial not only for his spiritual growth but also for societys future.

I see the power of yoga in its ability to bring back health, prosperity and harmony into people's lives. I believe that yoga, and its spiritual practices like meditation, have a place in ensuring a positive future for our society. And I am fully dedicated to my role in facilitating that.

Reflecting on how yoga has had an impact on his life beyond the physical practice, he said, Yoga has given me everything, and I am very grateful to my mom and my guru for guiding me on this path.

"Yoga showed me that peace of mind is not just an ideal, it is an achievable reality. Through yoga I have found a place in myself where I feel a deep sense of peace, connection and compassion and I strive every day to be conscious of that and to share that however I can.

Why is meditation important for today's people?

In this modern life we give our attention to everything outside...every problem and challenge we face is difficult because we have become disconnected from that inner source.

Through meditation, Rampersadsingh has found a deep sense of peace and aims to help others achieve the same.

He said the most immediate benefit of meditation for anyone, even if just starting off, is stress relief.

It gives a sense of relaxation and ease to help you rest and recover. As you go a little deeper it will help you to become healthier, manage your emotions, and uplift your thinking.

When you commit to yoga as a lifestyle, It will lead you to spiritual connection and insight to help you live in alignment with your life purpose and to reveal your full potential.

Looking ahead, he plans to continue writing and expand his teachings through coaching, workshops, and retreats. He hopes to see a greater appreciation for the spiritual aspects of yoga and meditation in the coming years, both locally and internationally.

To those new to yoga and meditation, he offered this advice: Practise, and all is coming to you.

For the hesitant, he encourages starting the journey with an open heart and finding a teacher who resonates with them, and he emphasises the importance of daily choices in cultivating wellness and spiritual connection.

Start Meditating Today is available in bookstores and directly from the author.

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Yoga instructor launches book on meditation - TT Newsday

In the ever-evolving landscape of machine learning and artificial intelligence (AI), large language models (LLMs) have emerged as powerful tools for a wide range of natural language processing (NLP) tasks, including code generation. Among these cutting-edge models, Code Llama 70B stands out as a true heavyweight, boasting an impressive 70 billion parameters. Developed by Meta and now available on Amazon SageMaker, this state-of-the-art LLM promises to revolutionize the way developers and data scientists approach coding tasks.

Code Llama 70B is a variant of the Code Llama foundation model (FM), a fine-tuned version of Metas renowned Llama 2 model. This massive language model is specifically designed for code generation and understanding, capable of generating code from natural language prompts or existing code snippets. With its 70 billion parameters, Code Llama 70B offers unparalleled performance and versatility, making it a game-changer in the world of AI-assisted coding.

Mixtral 8x7B is a state-of-the-art sparse mixture of experts (MoE) foundation model released by Mistral AI. It supports multiple use cases such as text summarization, classification, text generation, and code generation. It is an 8x model, which means it contains eight distinct groups of parameters. The model has about 45 billion total parameters and supports a context length of 32,000 tokens. MoE is a type of neural network architecture that consists of multiple experts where each expert is a neural network. In the context of transformer models, MoE replaces some feed-forward layers with sparse MoE layers. These layers have a certain number of experts, and a router network selects which experts process each token at each layer. MoE models enable more compute-efficient and faster inference compared to dense models.

Key features and capabilities of Code Llama 70B and Mixtral 8x7B include:

Amazon SageMaker, a fully managed machine learning service, provides a seamless integration with Code Llama 70B, enabling developers and data scientists to use its capabilities with just a few clicks. Heres how you can get started:

The following figure showcases how code generation can be done using the Llama and Mistral AI Models on SageMaker presented in this blog post.

You first deploy a SageMaker endpoint using an LLM from SageMaker JumpStart. For the examples presented in this article, you either deploy a Code Llama 70 B or a Mixtral 8x7B endpoint. After the endpoint has been deployed, you can use it to generate code with the prompts provided in this article and the associated notebook, or with your own prompts. After the code has been generated with the endpoint, you can use a notebook to test the code and its functionality.

In this section, you sign up for an AWS account and create an AWS Identity and Access Management (IAM) admin user.

If youre new to SageMaker, we recommend that you read What is Amazon SageMaker?.

Use the following hyperlinks to finish setting up the prerequisites for an AWS account and Sagemaker:

With the prerequisites complete, youre ready to continue.

The Mixtral 8x7B and Code Llama 70B models requires an ml.g5.48xlarge instance. SageMaker JumpStart provides a simplified way to access and deploy over 100 different open source and third-party foundation models. In order to deploy an endpoint using SageMaker JumpStart, you might need to request a service quota increase to access an ml.g5.48xlarge instance for endpoint use. You can request service quota increases through the AWS console, AWS Command Line Interface (AWS CLI), or API to allow access to those additional resources.

While Code Llama excels at generating simple functions and scripts, its capabilities extend far beyond that. The models can generate complex code for advanced applications, such as building neural networks for machine learning tasks. Lets explore an example of using Code Llama to create a neural network on SageMaker. Let us start with deploying the Code Llama Model through SageMaker JumpStart.

Additional details on deployment can be found in Code Llama 70B is now available in Amazon SageMaker JumpStart

Note: This blog post section contains code that was generated with the assistance of Code Llama70B powered by Amazon Sagemaker.

Let us walk through a code generation example with Code Llama 70B where you will generate a transformer model in python using Amazon SageMaker SDK.

Prompt:

Response:

Code Llama generates a Python script for training a Transformer model on the sample dataset using TensorFlow and Amazon SageMaker.

Code example: Create a new Python script (for example, code_llama_inference.py) and add the following code. Replace with the actual inference endpoint name provided by SageMaker JumpStart:

Save the script and run it:

python code_llama_inference.py

The script will send the provided prompt to the Code Llama 70B model deployed on SageMaker, and the models response will be printed to the output.

Example output:

Input

> Output

You can modify the prompt variable to request different code generation tasks or engage in natural language interactions with the model.

This example demonstrates how to deploy and interact with the Code Llama 70B model on SageMaker JumpStart using Python and the AWS SDK. Because the model might be prone to minor errors in generating the response output, make sure you run the code. Further, you can instruct the model to fact-check the output and refine the model response in order to fix any other unnecessary errors in the code. With this setup, you can leverage the powerful code generation capabilities of Code Llama 70B within your development workflows, streamlining the coding process and unlocking new levels of productivity. Lets take a look at some additional examples.

Lets walk through some other complex code generation scenarios. In the following sample, were running the script to generate a Deep Q reinforcement learning (RL) agent for playing the CartPole-v0 environment.

The following prompt was tested on Code Llama 70B to generate a Deep Q RL agent adept in playing CartPole-v0 environment.

Prompt:

Response: Code Llama generates a Python script for training a DQN agent on the CartPole-v1 environment using TensorFlow and Amazon SageMaker as showcased in our GitHub repository.

In this scenario, you will generate a sample python code for distributed machine learning training on Amazon SageMaker using Code Llama 70B.

Prompt:

Response: Code Llama generates a Python script for distributed training of a deep neural network on the ImageNet dataset using PyTorch and Amazon SageMaker. Additional details are available in our GitHub repository.

Compared to traditional LLMs, Mixtral 8x7B offers the advantage of faster decoding at the speed of a smaller, parameter-dense model despite containing more parameters. It also outperforms other open-access models on certain benchmarks and supports a longer context length.

Additional details on deployment can be found in Mixtral-8x7B is now available in Amazon SageMaker JumpStart.

Hyperparameters are external configuration variables that data scientists use to manage machine learning model training. Sometimes called model hyperparameters, the hyperparameters are manually set before training a model. Theyre different from parameters, which are internal parameters automatically derived during the learning process and not set by data scientists. Hyperparameters directly control model structure, function, and performance.

When you build complex machine learning systems like deep learning neural networks, exploring all the possible combinations is impractical. Hyperparameter tuning can accelerate your productivity by trying many variations of a model. It looks for the best model automatically by focusing on the most promising combinations of hyperparameter values within the ranges that you specify. To get good results, you must choose the right ranges to explore.

SageMaker automatic model tuning (AMT) finds the best version of a model by running many training jobs on your dataset. To do this, AMT uses the algorithm and ranges of hyperparameters that you specify. It then chooses the hyperparameter values that creates a model that performs the best, as measured by a metric that you choose.

Note: This blog post section contains code that was generated with the assistance of Mixtral 8X7B model, powered by Amazon Sagemaker.

Prompt:

Response:

There are instances where users need to convert code written in one programing language to another. This is known as a cross-language transformation task, and foundation models can help automate the process.

Prompt:

Response:

This Python code uses a built-in list data structure instead of the Java ArrayList class. The code above is more idiomatic and efficient in Python.

The AWS Cloud Development Kit (AWS CDK) is an open-source software development framework for defining cloud infrastructure as code with modern programming languages and deploying it through AWS CloudFormation.

The three-tier architecture pattern provides a general framework to ensure decoupled and independently scalable application components can be separately developed, managed, and maintained (often by distinct teams). A three-tier architecture is the most popular implementation of a multi-tier architecture and consists of a single presentation tier, logic tier, and data tier:

Prompt:

Response:

The following are some additional considerations when implementing these models:

Delete the model endpoints deployed using Amazon SageMaker for Code Llama and Mistral to avoid incurring any additional costs in your account.

Shut down any SageMaker Notebook instances that were created for deploying or running the examples showcased in this blog post to avoid any notebook instance costs associated with the account.

The combination of exceptional capabilities from foundation models like Code Llama 70B and Mixtral 8x7B and the powerful machine learning platform of Sagemaker, presents a unique opportunity for developers and data scientists to revolutionize their coding workflows. The cutting-edge capabilities of FMs empower customers to generate high-quality code, infill missing sections, and engage in natural language interactions, all while using the scalability, security, and compliance of AWS.

The examples highlighted in this blog post demonstrate these models advanced capabilities in generating complex code for various machine learning tasks, such as natural language processing, reinforcement learning, distributed training, and hyperparameter tuning, all tailored for deployment on SageMaker. Developers and data scientists can now streamline their workflows, accelerate development cycles, and unlock new levels of productivity in the AWS Cloud.

Embrace the future of AI-assisted coding and unlock new levels of productivity with Code Llama 70B and Mixtral 8x7B on Amazon SageMaker. Start your journey today and experience the transformative power of this groundbreaking language model.

Shikhar Kwatrais an AI/ML Solutions Architect at Amazon Web Services based in California. He has earned the title of one of the Youngest Indian Master Inventors with over 500 patents in the AI/ML and IoT domains. Shikhar aids in architecting, building, and maintaining cost-efficient, scalable cloud environments for the organization, and supports the GSI partners in building strategic industry solutions on AWS. Shikhar enjoys playing guitar, composing music, and practicing mindfulness in his spare time.

Jose Navarro is an AI/ML Solutions Architect at AWS based in Spain. Jose helps AWS customersfrom small startups to large enterprisesarchitect and take their end-to-end machine learning use cases to production. In his spare time, he loves to exercise, spend quality time with friends and family, and catch up on AI news and papers.

Farooq Sabiris a Senior Artificial Intelligence and Machine Learning Specialist Solutions Architect at AWS. He holds PhD and MS degrees in Electrical Engineering from the University of Texas at Austin and an MS in Computer Science from Georgia Institute of Technology. He has over 15 years of work experience and also likes to teach and mentor college students. At AWS, he helps customers formulate and solve their business problems in data science, machine learning, computer vision, artificial intelligence, numerical optimization, and related domains. Based in Dallas, Texas, he and his family love to travel and go on long road trips.

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Researchers who had been using Fitbit data to help predict surgical outcomes have a new method to more accurately gauge how patients may recover from spine surgery.

Using machine-learning techniques, researchers worked to develop a way to more accurately predict recovery from lumbar spine surgery.

The results, published in the journal Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, show that their model outperforms previous models to predict spine surgery outcomes.

This is important because in lower back surgery and many other types of orthopedic operations, outcomes vary widely depending on the patients structural disease but also on varying physical and mental health characteristics across patients.

Surgical recovery is influenced by both physical and mental health before the operation. Some people may have excessive worry in the face of pain that can make pain and recovery worse. Others may suffer from physiological problems that worsen pain. If physicians can get a heads-up on the various pitfalls a patient faces, they can better tailor treatment plans.

By predicting the outcomes before the surgery, we can help establish some expectations and help with early interventions and identify high risk factors, says first author Ziqi Xu, a PhD student in the lab of Chenyang Lu, a professor in the McKelvey School of Engineering at Washington University in St. Louis.

Previous work in predicting surgery outcomes typically used patient questionnaires given once or twice in clinics, capturing a static slice of time.

It failed to capture the long-term dynamics of physical and psychological patterns of the patients, Xu says. Prior work training machine-learning algorithms focused on just one aspect of surgery outcome but ignored the inherent multidimensional nature of surgery recovery, she adds.

Researchers have used mobile health data from Fitbit devices to monitor and measure recovery and compare activity levels over time. But the new research has shown that activity data, plus longitudinal assessment data, is more accurate in predicting how the patient will do after surgery, says Jacob Greenberg, an assistant professor of neurosurgery at the School of Medicine.

The current work offers a proof of principle showing that, with multimodal machine learning, doctors can see a more accurate big picture of the interrelated factors that affect recovery. Before beginning this work, the team first laid out the statistical methods and protocol to ensure they were feeding the artificial intelligence system the right balanced diet of data.

Previously, the team had published work in the journal Neurosurgery showing for the first time that patient-reported and objective wearable measurements improve predictions of early recovery compared to traditional patient assessments.

In addition to Greenberg and Xu, Madelynn Frumkin, a PhD student studying psychological and brain sciences in Thomas Rodebaughs laboratory, was a co-first author on that work. Wilson Zack Ray, a professor of neurosurgery at the School of Medicine, was co-senior author, along with Rodebaugh and Lu. Rodebaugh is now at the University of North Carolina at Chapel Hill.

In that research, they show that Fitbit data can be correlated with multiple surveys that assess a persons social and emotional state. They collected that data via ecological momentary assessments (EMAs) that employ smartphones to give patients frequent prompts to assess mood, pain levels, and behavior multiple times throughout day.

We combine wearables, EMA, and clinical records to capture a broad range of information about the patients, from physical activities to subjective reports of pain and mental health, and to clinical characteristics, Lu says.

Greenberg adds that state-of-the-art statistical tools that Rodebaugh and Frumkin have helped advance, such as Dynamic Structural Equation Modeling, were key in analyzing the complex, longitudinal EMA data.

For the most recent study, they took all those factors and developed a new machine-learning technique of Multi-Modal Multi-Task Learning to effectively combine these different types of data to predict multiple recovery outcomes.

In this approach, the AI learns to weigh the relatedness among the outcomes while capturing their differences from the multimodal data, Lu adds.

This method takes shared information on interrelated tasks of predicting different outcomes and then leverages the shared information to help the model understand how to make an accurate prediction, according to Xu.

It all comes together in the final package, producing a predicted change for each patients post-operative pain interference and physical function score.

Greenberg says the study is ongoing as the researchers continue to fine-tune their models so they can take more detailed assessments, predict outcomes and, most notably, understand what types of factors can potentially be modified to improve longer-term outcomes.

Funding for the study came from AO Spine North America, the Cervical Spine Research Society, the Scoliosis Research Society, the Foundation for Barnes-Jewish Hospital, Washington University/BJC Healthcare Big Ideas Competition, the Fullgraf Foundation, and the National Institute of Mental Health.

Source: Washington University in St. Louis

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AI better predicts back surgery outcomes - Futurity: Research News

The most underrated area of innovation in artificial intelligence is not in computing, nor is it in the development of algorithms or techniques for data collection. It is in the human ability to recast problems in terms of predictions.

Leading economist and academic Ajay Agrawal told the Fiduciary Investors Symposium in Toronto that it helps to think of AI and machine learning as simply a drop in the cost of prediction.

Agrawal serves as the Geoffrey Taber Chair in Entrepreneurship and Innovation at the University of Torontos Rotman School of Management, as well as being aProfessor of Strategic Management.

AI is computational statistics that does prediction, Agrawal said.

Thats all it is. And so, on the one hand, that seems very limiting. On the other hand, the thing thats so remarkable about it is all the things weve discovered that we can do with high fidelity prediction.

Agrawal said prediction is, in simple terms, taking information you have to generate information you dont have. And its the creativity of people to recast problems, that none of us in this room characterised as prediction problems, into prediction that underpins developments in and the potential of AI, he said.

Five years ago, probably nobody in this room would have said driving is a prediction problem.

Very few people in the room would have said translation is a prediction problem. Very few of you would have said replying to email is a prediction problem. But thats precisely how were solving all those things today.

Whether its predictive text when replying to an email or enhancing investment performance, the supporting AI systems are all implementations of statistics and prediction, Agrawal said.

These prediction models reached a zenith in large language models (LLMs), where machines were trained on how to predict the next most likely word in a sequence of words that made up sentences, paragraphs and whole responses.

If you think about language, lets say English, every book, every poem, every scripture that youve ever read, is a resequencing of the samecharacters: 26 letters, a few punctuation marks just re-sequenced over and over again makes all the books. What if we could do that with actions? Agrawal said.

The principles of LLMs (next most likely word) are now being applied to large behavioural models robots by training them to predict the next most likely verb or action.

In that case, we could take all the tasks think about everyone that you know, every job they do, and every job probably has 30 or 40 different tasks, so theres hundreds of thousands of tasks. But what if all those tasks are just really sequences of a small number of verbs?

So what theyre doing is theyre training that robots to do a handful verbs 50, 80, 120 verbs. Then you give the robot a prompt, just like chat GPT. You say to the robot, can you please unpack those boxes and put the tools on the shelf? The robot hears the prompt, and then predicts what is the optimal sequence of verbs in order to complete the task.

It is, Agrawal said, another application of prediction.

Agrawal said that businesses and industries are now facing a tidal wave of problems that have been recast as prediction problems.

So we now are pointing machine intelligence at many of these.

The problem is, it has come so hard and so fast, that people seem to be struggling with where do we start? And how do we actually point this towards something useful?

Agrawal said it pays to be very specific about the metric or the performance measure that needs to be improved, and then [point] the AI at that.

AIs are mathematical optimisers, they have to know what theyre optimising towards, he said.

If the problem is a tidal wave of new solutions available, and the problem is we dont know how to harness it, here is a way to think about the solution a short-term and a long-term strategy.

Agrawal said short-term strategies are basically productivity enhancements. Theyre deployable within a year, aim for 20 per cent productivity gains, and have a payback period of no more than two years.

And heres the key point, no change in the workflow, he said.

In other words, its truly a technology project where you just drop it in, but the rest of the system stays the same.

Long-term strategies take longer to deploy but theyre genuine game-changers, offering gains 10 times or more greater than short-term deployments. But critically, they require a redesign of workflows. Agrawal said AI, like electricity, is a general-purpose technology,

a useful analogy is when factories were first electrified and started to move away from stream-powered engines.

In the first 20 years after electricity was invented, there was very low take-up less than 3 per cent of factories used electricity, and when they did, the main value propositionwas it will reduce your input costs by doing things like replacing gas lamps.

Nobody wanted to tear apart their existing infrastructure in order to have that marginal benefit, Agrawal said.

The only ones that were experimenting with electricity were entrepreneurs building new factories, and even then, most of them said, No, I want to stick with what I know in terms of factory design.

But a few entrepreneurs realised there was a chance to completely reimagine and redesign a factory that was powered by electricity, because no longer was it dependent on transmitting power from engines outside the factory via long steel shafts to drive the factory machinery.

When the shafts became obsolete, so did the large columns inside the factories to support them. And that opened the door to lightweight, lower-cost construction, and factory design and layout changed to having everything on one level.

They redesigned the entire workflow, Agrawal said.

The machines, the materials, the material handling, the people flow, everything [was] redesigned. Some of the factories got up to 600 per cent productivity lift.

Agrawal said initially, the productivity differences between electrified and non-electrified factories were very small.

You could be operating a non-electrified factory and think those guys who want the newfangled electricity, its more trouble than its worth, he said.

But the but the productivity benefits just started taking off from electricity.

Now were seeing the same thing with machine intelligence [and] the adoption rate of AI.

However, Agrawal said the characteristic that makes AI different from every other tool weve ever had in human history, is this the only one that learns from us.

He said this explains the headlong development rush and the commitment of so much capital to the technology.

The way AI works is that whoever gets an early lead, their AI gets better; when their AI gets better, they get more users; when they get more users, they get more data; when they get more data, then the AI the prediction improves, he said.

And so, once they get that flywheel turning, it gets very hard to catch up to them.

Agrawal said AI and machine learning is developing so quickly its virtually impossible for companies and businesses to keep up, let alone implement and adapt.

The thing I would pay attention to is not so much the technology capability, because obviously thats important and its moving quickly, he said.

But what Im watching are the unit economics of the companies who are first experimenting with it, and then putting it into production, he said.

Cost just keeps going down because the AI is learning and getting better. And so that, like my sense there is, just pay very laser-close attention to the unit economics of what it costs to do a thing.

And you can go right down the stack of every good and service watching how, when you start applying these machine intelligence solutions to that thing, do the unit economics change?

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How to think about the economics of AI - Top1000funds.com