The Straits Times Business News July 25, 2023 11:11 PMMr Yao Hsiao Tung, who bagged the top Businessman of the Year award, was one of five SBA winners. Go to Source 25/07/2023 - 18:03 / Twitter: @hoffeldtcom

The Straits Times Business News July 25, 2023 10:36 PMThe IMF raised its 2023 global growth forecast to 3 per cent from 2.8 per cent. Go to Source 25/07/2023 - 18:03 / Twitter: @hoffeldtcom

The Straits Times Business News July 25, 2023 6:55 PMThe company announced the news in a bourse filing on Tuesday. Go to Source 25/07/2023 - 15:02 / Twitter: @hoffeldtcom

The Straits Times Business News July 25, 2023 8:48 AMUncertainties remain over the timing of any potential rebound in the key chip sector. Go to Source 25/07/2023 - 03:05 / Twitter: @hoffeldtcom

US Top News and Analysis Elon Musk's rebranding of Twitter to X in pursuit of becoming a super app leaves the already vulnerable business at risk of further deterioration. Go to Source 25/07/2023 - 00:04 / Twitter: @hoffeldtcom

The Straits Times Business News July 25, 2023 4:00 AMSingapore’s food bank pioneer hopes to curb tendency to toss food – with a little help from inflation and donations. Go to Source 25/07/2023 - 00:04 / Twitter: @hoffeldtcom

MIT News - Artificial intelligence As the U.S. Coast Guard (USCG) icebreaker Healy takes part in a voyage across the North Pole this summer, it is capturing images of the Arctic to further the study of this rapidly changing region. Lincoln Laboratory researchers installed a camera system aboard the Healy while at port in Seattle before it embarked on a three-month science mission on July 11. The resulting dataset, which will be one of the first of its kind, will be used to develop artificial intelligence tools that can analyze Arctic imagery. "This dataset not only can help mariners navigate more safely and operate more efficiently, but also help protect our nation by providing critical maritime domain awareness and an improved understanding of how AI analysis can be brought to bear in this challenging and unique environment," says Jo Kurucar, a researcher in Lincoln Laboratory's AI Software Architectures and Algorithms Group, which led this project. As the planet warms and sea ice melts, Arctic passages are opening up to more traffic, both to military vessels and ships conducting illegal fishing. These movements may pose national security challenges to the United States. The opening Arctic also leaves questions about how its climate, wildlife, and geography are changing. Today, very few imagery datasets of the Arctic exist to study these changes. Overhead images from satellites or aircraft can only provide limited information about the environment. An outward-looking camera attached to a ship can capture more details of the setting and different angles of objects, such as other ships, in the scene. These types of images can then be used to train AI computer-vision tools, which can help the USCG plan naval missions and automate analysis. According to Kurucar, USCG assets in the Arctic are spread thin and can benefit greatly from AI...

The Straits Times Business News July 24, 2023 4:10 PMThe Amazon programme is a collaboration with EnterpriseSG and Singapore Business Federation. Go to Source 24/07/2023 - 12:02 / Twitter: @hoffeldtcom

The Straits Times Business News July 24, 2023 9:25 AMWeak global demand and souring confidence weighed on business in the world’s third-largest economy. Go to Source 24/07/2023 - 06:03 / Twitter: @hoffeldtcom

Google AI Blog Posted by Cat Armato, Program Manager, Google Groups across Google actively pursue research in the field of machine learning (ML), ranging from theory and application. We build ML systems to solve deep scientific and engineering challenges in areas of language, music, visual processing, algorithm development, and more. We aim to build a more collaborative ecosystem with the broader ML research community through open-sourcing tools and datasets, publishing our work, and actively participating in conferences. Google is proud to be a Diamond Sponsor of the 40th International Conference on Machine Learning (ICML 2023), a premier annual conference, which is being held this week in Honolulu, Hawaii. As a leader in ML research, Google has a strong presence at this year’s conference with over 120 accepted papers and active involvement in a number of workshops and tutorials. Google is also proud to be a Platinum Sponsor for both the LatinX in AI and Women in Machine Learning workshops. We look forward to sharing some of our extensive ML research and expanding our partnership with the broader ML research community. Registered for ICML 2023? We hope you’ll visit the Google booth to learn more about the exciting work, creativity, and fun that goes into solving a portion of the field’s most interesting challenges. Visit the @GoogleAI Twitter account to find out about Google booth activities (e.g., demos and Q&A sessions). See Google DeepMind’s blog to learn about their technical participation at ICML 2023. Take a look below to learn more about the Google research being presented at ICML 2023 (Google affiliations in bold). Board and Organizing Committee Board Members include: Corinna Cortes, Hugo Larochelle Tutorial Chairs include: Hanie Sedghi Google Research booth activities Presenters: Bryan Perozzi, Anton Tsitsulin, Brandon Mayer Title: Unsupervised Graph Embedding @ Google (paper, EXPO workshop) Tuesday,...

Coronavirus | The Guardian Symptoms of infection can last two years, but researchers find no lasting cognitive impairment after individuals fully recover The so-called “brain fog” symptom associated with long Covid is comparable to ageing 10 years, researchers have suggested.In a study by King’s College London, researchers investigated the impact of Covid-19 on memory and found cognitive impairment highest in individuals who had tested positive and had more than three months of symptoms. Continue reading... Go to Source 21/07/2023 - 21:02 /Geneva Abdul Twitter: @hoffeldtcom

HR Daily Well-trained AI is a far better predictor of a "great hire" than all the tests and interviews developed by humans, yet HR practitioners remain hesitant to fully incorporate it in their organisations, according to new research from the Josh Bersin Company. Based on insights from senior AI-aware executives, engineers, product leaders, and global HR leaders, the research has uncovered "clear gaps in confidence and understanding linked to AI technology and its potential to deliver novel HR and talent management insights". "Rather than try to preach the basics of AI engineering, we want to help HR leaders become more comfortable with the technology and what it can do," says HR thought leader and advisor Josh Bersin... Go to Source 21/07/2023 - 09:02 /HR Daily Twitter: @hoffeldtcom

The Straits Times Business News July 20, 2023 3:14 PMFiscal 2023 growth forecast lowered to 1.3 per cent from 1.5 per cent previously. Go to Source 20/07/2023 - 12:01 / Twitter: @hoffeldtcom

NIMH News Feed In this webinar, researchers will present findings on identifying modifiable targets and mechanisms of action at the individual, family, and systems levels to improve mental health services and inform the development and testing of theory-based interventions that address mental health disparities in bi+ populations. Go to Source 20/07/2023 - 09:05 /National Institute of Mental Health Twitter: @hoffeldtcom

AWS Machine Learning Blog Large language models (LLMs) can be used to analyze complex documents and provide summaries and answers to questions. The post Domain-adaptation Fine-tuning of Foundation Models in Amazon SageMaker JumpStart on Financial data describes how to fine-tune an LLM using your own dataset. Once you have a solid LLM, you’ll want to expose that LLM to business users to process new documents, which could be hundreds of pages long. In this post, we demonstrate how to construct a real-time user interface to let business users process a PDF document of arbitrary length. Once the file is processed, you can summarize the document or ask questions about the content. The sample solution described in this post is available on GitHub. Working with financial documents Financial statements like quarterly earnings reports and annual reports to shareholders are often tens or hundreds of pages long. These documents contain a lot of boilerplate language like disclaimers and legal language. If you want to extract the key data points from one of these documents, you need both time and some familiarity with the boilerplate language so you can identify the interesting facts. And of course, you can’t ask an LLM questions about a document it has never seen. LLMs used for summarization have a limit on the number of tokens (characters) passed into the model, and with some exceptions, these are typically no more than a few thousand tokens. That normally precludes the ability to summarize longer documents. Our solution handles documents that exceed an LLM’s maximum token sequence length, and make that document available to the LLM for question answering. Solution overview Our design has three important pieces: It has an interactive web application for business users to upload and process PDFs It uses the langchain library to split a large...

AWS Machine Learning Blog Amazon SageMaker Model Cards enable you to standardize how models are documented, thereby achieving visibility into the lifecycle of a model, from designing, building, training, and evaluation. Model cards are intended to be a single source of truth for business and technical metadata about the model that can reliably be used for auditing and documentation purposes. They provide a factsheet of the model that is important for model governance. Until now, model cards were logically associated to a model in the Amazon SageMaker Model Registry using model name match. However, when solving a business problem through a machine learning (ML) model, as customers iterate on the problem, they create multiple versions of the model and they need to operationalize and govern multiple model versions. Therefore, they need the ability to associate a model card to a particular model version. In this post, we discuss a new feature that supports integrating model cards with the model registry at the deployed model version level. We discuss the solution architecture and best practices for managing model card versions, and walk through how to set up, operationalize, and govern the model card integration with the model version in the model registry. Solution overview SageMaker model cards help you standardize documenting your models from a governance perspective, and the SageMaker model registry helps you deploy and operationalize ML models. The model registry supports a hierarchical structure for organizing and storing ML models with model metadata information. When an organization solves a business problem using ML, such as a customer churn prediction, we recommend the following steps: Create a model card for the business problem to be solved. Create a model package group for the business problem to be solved. Build, train, evaluate, and register the first version of the model package...

Coronavirus | The Guardian Six weeks of hearings have seen arguments about pandemic planning bound up with old battles over Brexit and austerity• Covid inquiry hears call for more cash for public healthSome witnesses made tearful apologies; others defiantly denied fault. After six weeks of hearings at the UK Covid-19 public inquiry, the evidence about the UK’s preparedness for the Covid pandemic is in.The nation was caught badly off guard. That much was probably obvious. By 1 March 2021 the UK had suffered more than 180 Covid deaths per 100,000 people; in South Korea, the number was just three. But after hearing the evidence, the bereaved families put it bluntly: we were “catastrophically unprepared”. Continue reading... Go to Source 19/07/2023 - 18:03 /Robert Booth Social affairs correspondent Twitter: @hoffeldtcom

Human Resources News - Human Resources News Headlines | Bizjournals.com A little distance can make the heart grow fonder — and sharpen business acumen. Before he joined the family business, Edward Logan spent a few years at management consulting firm Deloitte, an experience he has described as akin to a mini-MBA, looking inside many businesses and figuring out how to change their trajectory. That stint expanded his leadership skills and provided him with a wide range of experiences before he signed on with Sport Clips in 2010. A decade later in 2020, he succeeded… Go to Source 19/07/2023 - 18:03 /Will Anderson Twitter: @hoffeldtcom

The Straits Times Business News July 19, 2023 10:55 AMShe previously led the exchange’s global business expansion, public relations and marketing. Go to Source 19/07/2023 - 06:03 / Twitter: @hoffeldtcom

AWS Machine Learning Blog Amazon Lex is a service that allows you to quickly and easily build conversational bots (“chatbots”), virtual agents, and interactive voice response (IVR) systems for applications such as Amazon Connect. Artificial intelligence (AI) and machine learning (ML) have been a focus for Amazon for over 20 years, and many of the capabilities that customers use with Amazon are driven by ML. Today, large language models (LLMs) are transforming the way developers and enterprises solve historically complex challenges related to natural language understanding (NLU). We announced Amazon Bedrock recently, which democratizes Foundational Model access for developers to easily build and scale generative AI-based applications, using familiar AWS tools and capabilities. One of the challenges enterprises face is to incorporate their business knowledge into LLMs to deliver accurate and relevant responses. When leveraged effectively, enterprise knowledge bases can be used to deliver tailored self-service and assisted-service experiences, by delivering information that helps customers solve problems independently and/or augmenting an agent’s knowledge. Today, a bot developer can improve self-service experiences without utilizing LLMs in a couple of ways. First, by creating intents, sample utterances, and responses, thereby covering all anticipated user questions within an Amazon Lex bot. Second, developers can also integrate bots with search solutions, which can index documents stored across a wide range of repositories and find the most relevant document to answer their customer’s question. These methods are effective, but require developer resources making getting started difficult. One of the benefits offered by LLMs is the ability to create relevant and compelling conversational self-service experiences. They do so by leveraging enterprise knowledge base(s) and delivering more accurate and contextual responses. This blog post introduces a powerful solution for augmenting Amazon Lex with LLM-based FAQ features using the Retrieval Augmented Generation (RAG). We will review how the...

Coronavirus | The Guardian More than a quarter of routes in English county and rural areas have been lost over 10 yearsEndangered rural bus services have dwindled to a new low after losing out on funding after the pandemic, analysis for councils has shown.More than a quarter of routes in county and rural areas of England have been lost in the past decade, with passenger numbers falling sharply. Continue reading... Go to Source 19/07/2023 - 03:03 /Gwyn Topham Transport correspondent Twitter: @hoffeldtcom

AWS Machine Learning Blog Spam emails, also known as junk mail, are sent to a large number of users at once and often contain scams, phishing content, or cryptic messages. Spam emails are sometimes sent manually by a human, but most often they are sent using a bot. Examples of spam emails include fake ads, chain emails, and impersonation attempts. There is a risk that a particularly well-disguised spam email may land in your inbox, which can be dangerous if clicked on. It’s important to take extra precautions to protect your device and sensitive information. As technology is improving, the detection of spam emails becomes a challenging task due to its changing nature. Spam is quite different from other types of security threats. It may at first appear like an annoying message and not a threat, but it has an immediate effect. Also spammers often adapt new techniques. Organizations who provide email services want to minimize spam as much as possible to avoid any damage to their end customers. In this post, we show how straightforward it is to build an email spam detector using Amazon SageMaker. The built-in BlazingText algorithm offers optimized implementations of Word2vec and text classification algorithms. Word2vec is useful for various natural language processing (NLP) tasks, such as sentiment analysis, named entity recognition, and machine translation. Text classification is essential for applications like web searches, information retrieval, ranking, and document classification. Solution overview This post demonstrates how you can set up email spam detector and filter spam emails using SageMaker. Let’s see how a spam detector typically works, as shown in the following diagram. Emails are sent through a spam detector. An email is sent to the spam folder if the spam detector detects it as spam. Otherwise, it’s sent to the customer’s inbox. We walk...

Coronavirus | The Guardian ‘Alarming’ reports of sudden rise in feline infectious peritonitis thought to point to more virulent strainThousands of cats have died in Cyprus, according to experts who are warning that a more virulent strain of a feline coronavirus is causing severe illness. Separately, dozens of cats have died after being infected with avian flu in Poland.The reports have raised questions about whether there is any connection between the rises in deaths and whether, given that many have pet cats at home, there is any evidence of an increased risk to people. Continue reading... Go to Source 18/07/2023 - 18:04 /Hannah Devlin and Linda Geddes Twitter: @hoffeldtcom

Coronavirus | The Guardian Campaign groups for bereaved in all UK nations said progress of pandemic showed country was not preparedPeople who died with Covid were treated like “toxic waste”, bereaved families have told the UK Covid-19 public inquiry, as they expressed their determination to channel their “grief, frustration and heartbreak” into making the UK better prepared for future pandemics.Representatives of campaign groups from England, Scotland, Wales and Northern Ireland told the inquiry how widespread infection in hospitals and care homes, failures to use PPE properly, the use of do not attempt cardiopulmonary resuscitation orders and isolation of vulnerable people all showed how the nations were not properly prepared. Continue reading... Go to Source 18/07/2023 - 18:04 /Robert Booth Social affairs correspondent Twitter: @hoffeldtcom

The Straits Times Business News July 18, 2023 8:14 PMA spokesman said SingPost intends to complete the strategic review within the current financial year. Go to Source 18/07/2023 - 15:06 / Twitter: @hoffeldtcom

Coronavirus | The Guardian Exclusive: Data analysis shows people severely penalised for relatively minor infractions of coronavirus lawsMore than 28,000 people in England and Wales have been convicted of breaches of Covid-19 regulations, despite the government’s insistence that it never intended to criminalise people for minor infractions during the pandemic.The convictions are for Covid-related offences, such as attendance at gatherings during lockdowns or arriving at airports without the proper evidence of a coronavirus test. Almost 16,000 of the convictions – or 55% – involved people under 30. Continue reading... Go to Source 18/07/2023 - 12:04 /Maeve McClenaghan Twitter: @hoffeldtcom

The Straits Times Business News July 18, 2023 3:00 PMCheck out Money FM's best weekly podcasts. Go to Source 18/07/2023 - 12:04 / Twitter: @hoffeldtcom

MIT News - Artificial intelligence Imagine purchasing a robot to perform household tasks. This robot was built and trained in a factory on a certain set of tasks and has never seen the items in your home. When you ask it to pick up a mug from your kitchen table, it might not recognize your mug (perhaps because this mug is painted with an unusual image, say, of MIT’s mascot, Tim the Beaver). So, the robot fails. “Right now, the way we train these robots, when they fail, we don’t really know why. So you would just throw up your hands and say, ‘OK, I guess we have to start over.’ A critical component that is missing from this system is enabling the robot to demonstrate why it is failing so the user can give it feedback,” says Andi Peng, an electrical engineering and computer science (EECS) graduate student at MIT. Peng and her collaborators at MIT, New York University, and the University of California at Berkeley created a framework that enables humans to quickly teach a robot what they want it to do, with a minimal amount of effort. When a robot fails, the system uses an algorithm to generate counterfactual explanations that describe what needed to change for the robot to succeed. For instance, maybe the robot would have been able to pick up the mug if the mug were a certain color. It shows these counterfactuals to the human and asks for feedback on why the robot failed. Then the system utilizes this feedback and the counterfactual explanations to generate new data it uses to fine-tune the robot. Fine-tuning involves tweaking a machine-learning model that has already been trained to perform one task, so it can perform a second, similar task. The researchers tested this technique in...

MIT News - Artificial intelligence The MIT Stephen A. Schwarzman College of Computing named Armando Solar-Lezama as the inaugural Distinguished College of Computing Professor, effective July 1.  Solar-Lezama is the first person appointed to this position generously endowed by Professor Jae S. Lim of the Department of Electrical Engineering and Computer Science (EECS). Established in the MIT Schwarzman College of Computing, the chair is being awarded to Solar-Lezama for being an outstanding faculty member who is recognized as a leader and innovator. “I’m pleased to make this appointment and recognize Armando for his remarkable contributions to MIT and the scientific community,” says Daniel Huttenlocher, dean of the MIT Schwarzman College of Computing and the Henry Ellis Warren Professor of Electrical Engineering and Computer Science. “I’m greatly appreciative of Professor Lim for his thoughtful gesture in creating this new chair in the college, providing us with the opportunity to acknowledge the accomplishments of our faculty.” Solar-Lezama, a professor of electrical engineering and computer science, leads the Computer-Aided Programming Group in the Computer Science and Artificial Intelligence Laboratory (CSAIL) that focuses on program synthesis, an area of research that lies at the intersection of programming systems and artificial intelligence. The group’s research ranges from designing new analysis techniques and automated reasoning mechanisms to developing new programming models that automate challenging aspects of programming. A member of the EECS faculty since 2008, Solar-Lezama, who also serves as the associate director and chief operating officer for CSAIL, is most interested in software synthesis and its applications to particular program domains such as high-performance computing. He first found this niche area of program synthesis as a graduate student at the University of California at Berkeley, for which his thesis project, a language called Sketch, treats program synthesis as a search problem in which the algorithms...

Coronavirus | The Guardian Sister and nephew rebuke presidential hopeful over ‘deplorable’ comments about ‘engineering’ of virus to target certain groupsFamily members of Democratic presidential hopeful Robert Kennedy Jr joined the White House on Monday in condemning his “deplorable” claim that Covid-19 was engineered to target some ethnic groups and spare others.The former attorney and nephew of John F Kennedy made the extraordinary assertion during a recent dinner in New York city, saying the virus was “targeted to attack Caucasians and Black people”. Continue reading... Go to Source 18/07/2023 - 00:01 /Richard Luscombe Twitter: @hoffeldtcom

Coronavirus | The Guardian Official figures show in a 15-month period at least 50% of disqualified bosses are accused of fraud or abuse of coronavirus support schemes More than half of all company directors struck off in Britain in the past 15 months were involved in alleged fraud or abuse of Covid-19 financial support schemes, official figures have revealed.There were 1,200 directors disqualified between 1 April last year and 30 June this year, with 611 of the cases involving abuse of Covid-19 schemes, mainly in relation to taxpayer-backed bounce-back loans. About £1.1bn of loans have already been flagged as suspected fraud or error. Continue reading... Go to Source 16/07/2023 - 12:07 /Jon Ungoed-Thomas and Sophie Smith Twitter: @hoffeldtcom

Coronavirus | The Guardian Researchers conclude lockdown babies are lagging behind after limited interaction during Covid restrictionsAt the age of two, babies born during the pandemic have similar behaviour and development compared with children who were born before Covid-19 arrived – with one exception. Their communication skills lag behind those of their predecessors.These are the intriguing findings of a study – carried out by researchers based at the Royal College of Surgeons in Ireland (RCSI) – which examined what life was like for babies born during the pandemic, and the implications for their health and development. Continue reading... Go to Source 16/07/2023 - 12:07 /Robin McKie Science Editor Twitter: @hoffeldtcom

US Top News and Analysis To start the year, it was a bold and minority position to predict the U.S. economy could land softly, that inflation would drop fast and the Federal Reserve would ease off the brake even while growth stayed resilient. Go to Source 15/07/2023 - 18:01 / Twitter: @hoffeldtcom

The Straits Times Business News July 15, 2023 7:30 PMRare earth resources are essential for decarbonisation and production of electric vehicles. Go to Source 15/07/2023 - 15:03 / Twitter: @hoffeldtcom

MIT News - Artificial intelligence Amid a huge amount of hype around generative AI, a new study from researchers at MIT sheds light on the technology’s impact on work, finding that it increased productivity for workers assigned tasks like writing cover letters, delicate emails, and cost-benefit analyses. The tasks in the study weren’t quite replicas of real work: They didn’t require precise factual accuracy or context about things like a company’s goals or a customer’s preferences. Still, a number of the study’s participants said the assignments were similar to things they’d written in their real jobs — and the benefits were substantial. Access to the assistive chatbot ChatGPT decreased the time it took workers to complete the tasks by 40 percent, and output quality, as measured by independent evaluators, rose by 18 percent. The researchers hope the study, which appears today in open-access form in the journal Science, helps people understand the impact that AI tools like ChatGPT can have on the workforce. “What we can say for sure is generative AI is going to have a big effect on white collar work,” says Shakked Noy, a PhD student in MIT’s Department of Economics, who co-authored the paper with fellow PhD student Whitney Zhang ’21. “I think what our study shows is that this kind of technology has important applications in white collar work. It’s a useful technology. But it’s still too early to tell if it will be good or bad, or how exactly it’s going to cause society to adjust.” Simulating work for chatbots For centuries, people have worried that new technological advancements would lead to mass automation and job loss. But new technologies also create new jobs, and when they increase worker productivity, they can have a net positive effect on the economy. “Productivity is front of...

The Straits Times Business News July 14, 2023 6:05 PMEligible trainees can have up to 90 per cent of the course fees subsidised by the Government. Go to Source 14/07/2023 - 15:02 / Twitter: @hoffeldtcom

The Straits Times Business News July 14, 2023 3:35 PMEmbedded insurance will become more customisable and convenient in the future. Go to Source 14/07/2023 - 12:02 / Twitter: @hoffeldtcom

MIT News - Artificial intelligence Imagine that a team of scientists has developed a machine-learning model that can predict whether a patient has cancer from lung scan images. They want to share this model with hospitals around the world so clinicians can start using it in diagnosis. But there’s a problem. To teach their model how to predict cancer, they showed it millions of real lung scan images, a process called training. Those sensitive data, which are now encoded into the inner workings of the model, could potentially be extracted by a malicious agent. The scientists can prevent this by adding noise, or more generic randomness, to the model that makes it harder for an adversary to guess the original data. However, perturbation reduces a model’s accuracy, so the less noise one can add, the better. MIT researchers have developed a technique that enables the user to potentially add the smallest amount of noise possible, while still ensuring the sensitive data are protected. The researchers created a new privacy metric, which they call Probably Approximately Correct (PAC) Privacy, and built a framework based on this metric that can automatically determine the minimal amount of noise that needs to be added. Moreover, this framework does not need knowledge of the inner workings of a model or its training process, which makes it easier to use for different types of models and applications. In several cases, the researchers show that the amount of noise required to protect sensitive data from adversaries is far less with PAC Privacy than with other approaches. This could help engineers create machine-learning models that provably hide training data, while maintaining accuracy in real-world settings. “PAC Privacy exploits the uncertainty or entropy of the sensitive data in a meaningful way,  and this allows us to add, in many...

Google AI Blog Posted by Jerry Wei, Student Researcher, and Denny Zhou, Principal Scientist, Google Research A key feature of human intelligence is that humans can learn to perform new tasks by reasoning using only a few examples. Scaling up language models has unlocked a range of new applications and paradigms in machine learning, including the ability to perform challenging reasoning tasks via in-context learning. Language models, however, are still sensitive to the way that prompts are given, indicating that they are not reasoning in a robust manner. For instance, language models often require heavy prompt engineering or phrasing tasks as instructions, and they exhibit unexpected behaviors such as performance on tasks being unaffected even when shown incorrect labels. In “Symbol tuning improves in-context learning in language models”, we propose a simple fine-tuning procedure that we call symbol tuning, which can improve in-context learning by emphasizing input–label mappings. We experiment with symbol tuning across Flan-PaLM models and observe benefits across various settings. Symbol tuning boosts performance on unseen in-context learning tasks and is much more robust to underspecified prompts, such as those without instructions or without natural language labels. Symbol-tuned models are much stronger at algorithmic reasoning tasks. Finally, symbol-tuned models show large improvements in following flipped-labels presented in-context, meaning that they are more capable of using in-context information to override prior knowledge. An overview of symbol tuning, where models are fine-tuned on tasks where natural language labels are replaced with arbitrary symbols. Symbol tuning relies on the intuition that when instruction and relevant labels are not available, models must use in-context examples to learn the task. Motivation Instruction tuning is a common fine-tuning method that has been shown to improve performance and allow models to better follow in-context examples. One shortcoming, however, is that models are not forced to...

BBC News - Business The owner of Anchor Brewing said it could not overcome the hit from the pandemic. Go to Source 13/07/2023 - 21:03 / Twitter: @hoffeldtcom

MIT News - Artificial intelligence Data, and more specifically using data, is not a new concept, but it remains an elusive one. It comes with terms like “the internet of things” (IoT) and “the cloud,” and no matter how often those are explained, smart people can still be confused. And then there’s the amount of information available and the speed with which it comes in. Software is omnipresent. It’s in coffeemakers and watches, gathering data every second. The question becomes how to take all the new technology and take advantage of the potential insights and analytics. It’s not a small ask. “Putting our arms around what digital transformation is can be difficult to do,” says Abel Sanchez. But as the executive director and research director of MIT’s Geospatial Data Center, that’s exactly what he does with his work in helping industries and executives shift their operations in order to make sense of their data and be able to use it to help their bottom lines. Handling the pace Data can lead to making better business decisions. That’s not a new or surprising insight, but as Sanchez says, people still tend to work off of intuition. Part of the problem is that they don’t know what to do with their available data, and there’s usually plenty of available data. Part of that problem is that there’s so much information being produced from so many sources. As soon as a person wakes up and turns on their phone or starts their car, software is running. It’s coming in fast, but because it’s also complex, “it outperforms people,” he says. As an example with Uber, once a person clicks on the app for a ride, predictive models start firing at the rate of 1 million per second. It’s all in order to optimize...

BBC News - Business The economy shrank by 0.1% in May and has barely grown since 2019 before the pandemic. Go to Source 13/07/2023 - 18:03 / Twitter: @hoffeldtcom

The Straits Times Business News July 13, 2023 11:23 PMData showed the British economy shrank by less than expected in May. Go to Source 13/07/2023 - 18:02 / Twitter: @hoffeldtcom

US Top News and Analysis Disney CEO Bob Iger appeared for an interview with CNBC's David Faber the morning after announcing a contract extension through 2026. Go to Source 13/07/2023 - 15:02 / Twitter: @hoffeldtcom

NIMH News Feed This webinar will review key factors for grant applicants to consider when developing plans related to protecting human subjects, as well as data safety and monitoring in clinical research studies funded by NIMH. Go to Source 13/07/2023 - 09:05 /National Institute of Mental Health Twitter: @hoffeldtcom

The Straits Times Business News July 13, 2023 10:04 AMTapping new opportunities in areas like digitalisation and sustainable living is crucial to Temasek’s growth. Go to Source 13/07/2023 - 06:03 / Twitter: @hoffeldtcom

Human Resources News - Human Resources News Headlines | Bizjournals.com Husch Blackwell hired a new CEO, who will take over leadership from Paule Eberle in February. Jamie Lawless has extensive professional services and law firm management experience. Go to Source 11/07/2023 - 21:04 /James Dornbrook Twitter: @hoffeldtcom

US Top News and Analysis North Carolina is again America's Top State for Business, led by a strong economy and workforce, earning the rare repeat No. 1 finish in the annual rankings. Go to Source 11/07/2023 - 18:05 / Twitter: @hoffeldtcom

The Straits Times Business News July 11, 2023 4:00 AMShe’s tackling fashion overconsumption and waste by making it easier for you to swop and recycle your unwanted clothes. Go to Source 11/07/2023 - 00:07 / Twitter: @hoffeldtcom

MIT News - Artificial intelligence Walking to a friend’s house or browsing the aisles of a grocery store might feel like simple tasks, but they in fact require sophisticated capabilities. That's because humans are able to effortlessly understand their surroundings and detect complex information about patterns, objects, and their own location in the environment. What if robots could perceive their environment in a similar way? That question is on the minds of MIT Laboratory for Information and Decision Systems (LIDS) researchers Luca Carlone and Jonathan How. In 2020, a team led by Carlone released the first iteration of Kimera, an open-source library that enables a single robot to construct a three-dimensional map of its environment in real time, while labeling different objects in view. Last year, Carlone’s and How’s research groups (SPARK Lab and Aerospace Controls Lab) introduced Kimera-Multi, an updated system in which multiple robots communicate among themselves in order to create a unified map. A 2022 paper associated with the project recently received this year’s IEEE Transactions on Robotics King-Sun Fu Memorial Best Paper Award, given to the best paper published in the journal in 2022. Carlone, who is the Leonardo Career Development Associate Professor of Aeronautics and Astronautics, and How, the Richard Cockburn Maclaurin Professor in Aeronautics and Astronautics, spoke to LIDS about Kimera-Multi and the future of how robots might perceive and interact with their environment. Q: Currently your labs are focused on increasing the number of robots that can work together in order to generate 3D maps of the environment. What are some potential advantages to scaling this system? How: The key benefit hinges on consistency, in the sense that a robot can create an independent map, and that map is self-consistent but not globally consistent. We’re aiming for the team to have a consistent...

The Straits Times Business News July 10, 2023 7:59 AMEven Singapore, which had credited the travel boom for ruling out a recession this year, has seen numbers disappoint. Go to Source 10/07/2023 - 03:04 / Twitter: @hoffeldtcom

Coronavirus | The Guardian Exclusive: Therapeutic Goods Administration documents reveal separate reports made in 2022 about two boys, aged six and seven, were falseGet our morning and afternoon news emails, free app or daily news podcastAustralia’s drug regulator received two reports of child deaths following vaccination against Covid-19 that turned out to be hoaxes.Therapeutic Goods Administration documents on fatal adverse events in children and adolescents following a Covid-19 vaccination published under freedom of information show that a report was made to the body in January 2022 that a seven-year-old boy died from “an adverse event following immunisation” with an unspecified brand of Covid vaccine.Sign up for Guardian Australia’s free morning and afternoon email newsletters for your daily news roundup Continue reading... Go to Source 09/07/2023 - 18:03 /Melissa Davey Medical editor Twitter: @hoffeldtcom

The Straits Times Business News July 09, 2023 5:00 AMThis is a cautionary tale on why you should always insist on the necessary paperwork being done. Go to Source 09/07/2023 - 00:02 / Twitter: @hoffeldtcom

Google AI Blog Posted by Sanjay Subramanian, PhD student, UC Berkeley, and Arsha Nagrani, Research Scientist, Google Research, Perception Team Visual question answering (VQA) is a machine learning task that requires a model to answer a question about an image or a set of images. Conventional VQA approaches need a large amount of labeled training data consisting of thousands of human-annotated question-answer pairs associated with images. In recent years, advances in large-scale pre-training have led to the development of VQA methods that perform well with fewer than fifty training examples (few-shot) and without any human-annotated VQA training data (zero-shot). However, there is still a significant performance gap between these methods and state-of-the-art fully supervised VQA methods, such as MaMMUT and VinVL. In particular, few-shot methods struggle with spatial reasoning, counting, and multi-hop reasoning. Furthermore, few-shot methods have generally been limited to answering questions about single images. To improve accuracy on VQA examples that involve complex reasoning, in “Modular Visual Question Answering via Code Generation,” to appear at ACL 2023, we introduce CodeVQA, a framework that answers visual questions using program synthesis. Specifically, when given a question about an image or set of images, CodeVQA generates a Python program (code) with simple visual functions that allow it to process images, and executes this program to determine the answer. We demonstrate that in the few-shot setting, CodeVQA outperforms prior work by roughly 3% on the COVR dataset and 2% on the GQA dataset. CodeVQA The CodeVQA approach uses a code-writing large language model (LLM), such as PALM, to generate Python programs (code). We guide the LLM to correctly use visual functions by crafting a prompt consisting of a description of these functions and fewer than fifteen “in-context” examples of visual questions paired with the associated Python code for them. To select these...

US Top News and Analysis Nonfarm payrolls were expected to increase by 240,000 and the unemployment rate to fall to 3.6% in June. Go to Source 07/07/2023 - 15:04 / Twitter: @hoffeldtcom

The Straits Times Business News July 07, 2023 8:20 PMThis will boost cooperation in sustainability, digitalisation, financial services and human capital development. Go to Source 07/07/2023 - 15:03 / Twitter: @hoffeldtcom

NIMH News Feed This webinar will provide an overview of research focused on building equitable STEM graduate programs that promote the admission, recruitment, and retention of diverse populations. Go to Source 07/07/2023 - 09:01 /National Institute of Mental Health Twitter: @hoffeldtcom

MIT News - Artificial intelligence Discovering new materials and drugs typically involves a manual, trial-and-error process that can take decades and cost millions of dollars. To streamline this process, scientists often use machine learning to predict molecular properties and narrow down the molecules they need to synthesize and test in the lab. Researchers from MIT and the MIT-Watson AI Lab have developed a new, unified framework that can simultaneously predict molecular properties and generate new molecules much more efficiently than these popular deep-learning approaches. To teach a machine-learning model to predict a molecule’s biological or mechanical properties, researchers must show it millions of labeled molecular structures — a process known as training. Due to the expense of discovering molecules and the challenges of hand-labeling millions of structures, large training datasets are often hard to come by, which limits the effectiveness of machine-learning approaches. By contrast, the system created by the MIT researchers can effectively predict molecular properties using only a small amount of data. Their system has an underlying understanding of the rules that dictate how building blocks combine to produce valid molecules. These rules capture the similarities between molecular structures, which helps the system generate new molecules and predict their properties in a data-efficient manner. This method outperformed other machine-learning approaches on both small and large datasets, and was able to accurately predict molecular properties and generate viable molecules when given a dataset with fewer than 100 samples. “Our goal with this project is to use some data-driven methods to speed up the discovery of new molecules, so you can train a model to do the prediction without all of these cost-heavy experiments,” says lead author Minghao Guo, a computer science and electrical engineering (EECS) graduate student. Guo’s co-authors include MIT-IBM Watson AI Lab research staff members Veronika Thost,...

The Straits Times Business News July 07, 2023 8:29 AMAn ongoing chip glut drives large losses in the tech giant’s key business despite a supply cut. Go to Source 07/07/2023 - 03:04 / Twitter: @hoffeldtcom

MIT News - Artificial intelligence Is it possible to build machine-learning models without machine-learning expertise? Jim Collins, the Termeer Professor of Medical Engineering and Science in the Department of Biological Engineering at MIT and the life sciences faculty lead at the Abdul Latif Jameel Clinic for Machine Learning in Health (Jameel Clinic), along with a number of colleagues decided to tackle this problem when facing a similar conundrum. An open-access paper on their proposed solution, called BioAutoMATED, was published on June 21 in Cell Systems. Recruiting machine-learning researchers can be a time-consuming and financially costly process for science and engineering labs. Even with a machine-learning expert, selecting the appropriate model, formatting the dataset for the model, then fine-tuning it can dramatically change how the model performs, and takes a lot of work.  “In your machine-learning project, how much time will you typically spend on data preparation and transformation?” asks a 2022 Google course on the Foundations of Machine Learning (ML). The two choices offered are either “Less than half the project time” or “More than half the project time.” If you guessed the latter, you would be correct; Google states that it takes over 80 percent of project time to format the data, and that’s not even taking into account the time needed to frame the problem in machine-learning terms. “It would take many weeks of effort to figure out the appropriate model for our dataset, and this is a really prohibitive step for a lot of folks that want to use machine learning or biology,” says Jacqueline Valeri, a fifth-year PhD student of biological engineering in Collins’s lab who is first co-author of the paper.  BioAutoMATED is an automated machine-learning system that can select and build an appropriate model for a given dataset and even take care of the...

Coronavirus | The Guardian Research suggests those aged 18 to 24 have been deeply affected by pandemic and then cost of living and healthcare crisesYoung adults are bearing the brunt of a “growing mental health crisis” in England, according to researchers who warn that levels of severe distress have risen steadily in adults since the start of the pandemic.The disturbing trend may be driven by an “unprecedented series of events” including the cost of living and healthcare crises and the impact of the pandemic itself, the researchers said, adding there was an urgent need to address the causes and improve funding for mental health services. Continue reading... Go to Source 06/07/2023 - 18:00 /Ian Sample Science editor Twitter: @hoffeldtcom

The Straits Times Business News July 06, 2023 6:44 PMAcross the broader market, losers beat gainers 338 to 196, after 1.15 billion securities worth $1.09 billion were traded. Go to Source 06/07/2023 - 15:05 / Twitter: @hoffeldtcom

MIT News - Artificial intelligence From cameras to self-driving cars, many of today’s technologies depend on artificial intelligence to extract meaning from visual information. Today’s AI technology has artificial neural networks at its core, and most of the time we can trust these AI computer vision systems to see things the way we do — but sometimes they falter. According to MIT and IBM research scientists, one way to improve computer vision is to instruct the artificial neural networks that they rely on to deliberately mimic the way the brain’s biological neural network processes visual images. Researchers led by MIT Professor James DiCarlo, the director of MIT’s Quest for Intelligence and member of the MIT-IBM Watson AI Lab, have made a computer vision model more robust by training it to work like a part of the brain that humans and other primates rely on for object recognition. This May, at the International Conference on Learning Representations, the team reported that when they trained an artificial neural network using neural activity patterns in the brain’s inferior temporal (IT) cortex, the artificial neural network was more robustly able to identify objects in images than a model that lacked that neural training. And the model’s interpretations of images more closely matched what humans saw, even when images included minor distortions that made the task more difficult. Comparing neural circuits Many of the artificial neural networks used for computer vision already resemble the multilayered brain circuits that process visual information in humans and other primates. Like the brain, they use neuron-like units that work together to process information. As they are trained for a particular task, these layered components collectively and progressively process the visual information to complete the task — determining, for example, that an image depicts a bear or a car or...

Coronavirus | The Guardian Inquiry hears of communication problems and lack of preparedness for pandemicCommunication from central government was so poor during parts of the Covid pandemic that directors of public health relied on TV and newspapers to find out about key decisions, the UK Covid public inquiry has heard.Government departments did not even have contact details for some of the 150 senior public health officials based in councils, said Prof Jim McManus, president of the Association of Directors of Public Health, who told the inquiry: “They physically couldn’t contact us.” Continue reading... Go to Source 05/07/2023 - 18:03 /Robert Booth Twitter: @hoffeldtcom

The Straits Times Business News July 05, 2023 12:12 PMSINGAPORE - ComfortDelgro (CD) is poised for a strong earnings recovery during the upcoming quarter and potential higher dividend payout ahead. Go to Source 05/07/2023 - 09:03 / Twitter: @hoffeldtcom

The Straits Times Business News Mixed-use development Odom is expected to meet the increased demand for office and residential spaces as Cambodia’s capital attracts foreign investment and talent.  Go to Source 05/07/2023 - 00:02 / Twitter: @hoffeldtcom