Wolfram can Plug into GPT for new SuperPowers

Saw this hinted at a while back. Wolfram Alpha has had unique analytic capabilities for some time, now you can link these to ChatGPT.  Via a plugin.   Apparently there is the ability to add other plugins as well. Thinking about some possibilities.   How to hinted at blow, note current restrictions with OpenAI updates.   Good intro to wolfram capabilities,  which were used by some in out enterprise,  most for component testing analytics.    Wolfram also gives you the bonus of some good integrated analytics visualization. The article below contains some very interesting examples.  And in addition describes how the neural nets of large language models relate to the Neural nets that Wolfram has been talking about for years relate.   All this is quite exciting,  but you may have to wait until Plugins are available in ChatGPT. 

ChatGPT Gets Its “Wolfram Superpowers”!

March 23, 2023

To enable the functionality described here, select and install the Wolfram plugin from within ChatGPT.

Note that this capability is so far available only to some ChatGPT Plus users; for more information, see OpenAI’s announcement.

In Just Two and a Half Months…

Early in January I wrote about the possibility of connecting ChatGPT to Wolfram|Alpha. And today—just two and a half months later—I’m excited to announce that it’s happened! Thanks to some heroic software engineering by our team and by OpenAI, ChatGPT can now call on Wolfram|Alpha—and Wolfram Language as well—to give it what we might think of as “computational superpowers”. It’s still very early days for all of this, but it’s already very impressive—and one can begin to see how amazingly powerful (and perhaps even revolutionary) what we can call “ChatGPT + Wolfram” can be.

Back in January, I made the point that, as an LLM neural net, ChatGPT—for all its remarkable prowess in textually generating material “like” what it’s read from the web, etc.—can’t itself be expected to do actual nontrivial computations, or to systematically produce correct (rather than just “looks roughly right”) data, etc. But when it’s connected to the Wolfram plugin it can do these things. So here’s my (very simple) first example from January, but now done by ChatGPT with “Wolfram superpowers” installed:

How far is it from Tokyo to Chicago?

It’s a correct result (which in January it wasn’t)—found by actual computation. And here’s a bonus: immediate visualization:

Show the path

How did this work? Under the hood, ChatGPT is formulating a query for Wolfram|Alpha—then sending it to Wolfram|Alpha for computation, and then “deciding what to say” based on reading the results it got back. You can see this back and forth by clicking the “Used Wolfram” box (and by looking at this you can check that ChatGPT didn’t “make anything up”):  .... '

Security Issues in AI Emerge

There seems to have been an urge to get some of these systems out before securing them.

ChatGPT bug leaked users' conversation histories  in the BBC

OpenAI launched ChatGPT last November    By Ben Derico       BBC News, San Francisco

A ChatGPT glitch allowed some users to see the titles of other users' conversations, the artificial intelligence chatbot's boss has said.

On social media sites Reddit and Twitter, users had shared images of chat histories that they said were not theirs.

OpenAI CEO Sam Altman said the company feels "awful", but the "significant" error had now been fixed.   Many users, however, remain concerned about privacy on the platform.

Millions of people have used ChatGPT to draft messages, write songs and even code since it launched in November of last year.  Each conversation with the chatbot is stored in the user's chat history bar where it can be revisited later.

Is the world prepared for the coming AI storm?

But as early as Monday, users began to see conversations appear in their history that they said they hadn't had with the chatbot,One user on Reddit shared a photo of their chat history including titles like "Chinese Socialism Development", as well as conversations in Mandarin.  

On Tuesday, the company told Bloomberg that it had briefly disabled the chatbot late on Monday to fix the error.  They also said that users had not been able to access the actual chats.

OpenAI's chief executive tweeted that there would be a "technical postmortem" soon. But the error has drawn concern from users who fear their private information could be released through the tool. The glitch seemed to indicate that OpenAI has access to user chats.

The company's privacy policy does say that user data, such as prompts and responses, may be used to continue training the model. But that data is only used after personally identifiable information has been removed. 

The blunder also comes just a day after Google unveiled its chatbot Bard to a group of beta testers and journalists. Google and Microsoft, a major investor in OpenAI, have been jostling for control of the burgeoning market for artificial intelligence tools. But the pace of new product updates and releases has many concerned missteps like these could be harmful or have unintended consequences.  ... ' 

ML Physics Platform NVIDIA Modulus is Open

 New things out of NVIDIA Resources, Fascinating,  Sample Uses?

Machine Learning Platform NVIDIA Modulus Is Now Open Source

By Bhoomi Gadhia, Ram Cherukuri and Kristen Perez

Physics-informed machine learning (physics-ML) is transforming high-performance computing (HPC) simulation workflows across disciplines, including computational fluid dynamics, structural mechanics, and computational chemistry. Because of its broad applications, physics-ML is well suited for modeling physical systems and deploying digital twins across industries ranging from manufacturing to climate sciences.

NVIDIA Modulus is a state-of-the-art physics-ML platform that blends physics with deep learning training data to build high-fidelity, parameterized surrogate models with near-real-time latency. The surrogate models built using NVIDIA Modulus help a wide range of solutions including weather forecasting, reducing power plant greenhouse gasses, and accelerating clean energy transitions.

NVIDIA Modulus customer success stories are proving the platform’s incredible utility across industries. However, physics-ML is a relatively new field in the deep learning arena, with significant challenges both at the research level as well as at the application front. This is due to the unique requirements needed to satisfy physics-ML rules:

The need for a deep learning model to obey the governing principles of a physical system.

The need for new deep learning model architectures for a specific class of problems, such as those that can satisfy fluid mechanics laws.

The need for generalizable model architectures and algorithms that can serve across different applications.

These challenges require innovation and research across several domains. More importantly, these problems require a strong collaboration between respective domains, industries, and deep learning experts. This level of collaboration requires tools and technologies that remove barriers between researchers, teams, and even industries, to enable the community to build on each other’s work.

Because simulations are critical to these disciplines and the industries that employ them, there is a demand for building and demonstrating confidence that AI can meet and surpass the current simulation approaches. This requires transparency so research can identify the limitations and provide breakthroughs to enable more transformative technologies.

Now, to facilitate the collaboration, transparency, and accountability needed, NVIDIA Modulus has become an open-source platform available for physics-ML.

Physics-ML open-source workflows

This new open-source environment provides significant benefits for AI developers and domain experts across industries in several ways:

Collaboration: An open-source workflow enables you to collaborate more easily with colleagues and share your work with a wider community. By making data, code, and methods openly accessible, you can work together more effectively to address complex physics-ML questions.

Transparency: Open-source workflows can increase the transparency and reproducibility of physics-ML research. By publishing code and data, you can enable other researchers to verify and replicate your results, which can help to build greater trust in the scientific findings.

Innovation: Open-source workflows can facilitate innovation by enabling you to build on other researchers’ work more easily. By providing access to a shared repository of tools and techniques, open-source workflows can help to accelerate the pace of discovery and enhance the quality of research outputs.

Accessibility: Open-source workflows can help to make research more accessible to a wider range of stakeholders, including drug development managers, national lab directors, policymakers, journalists, and members of the public. By providing clear, accessible information about physics-based modeling research, open-source workflows can help build greater awareness and understanding.

Overall, an open-source workflow can help AI developers and engineering and science domain experts to work more collaboratively, transparently, innovatively, and with greater accessibility to enhance the impact and relevance of their research.

Accessing NVIDIA Modulus open-source software

NVIDIA Modulus is available as open-source software (OSS) under the simple Apache 2.0 license. .... ' 

AI being used to cherry-pick organs for transplant

 AI being used to cherry-pick organs for transplant

By Duncan MacRae | March 2, 2023 | MarketingTech  in ArtificialIntelligence

Duncan is an award-winning editor with more than 20 years experience in journalism. Having launched his tech journalism career as editor of Arabian Computer News in Dubai, he has since edited an array of tech and digital marketing publications, including Computer Business Review, TechWeekEurope, Figaro Digital, Digit and Marketing Gazette.

A new method to assess the quality of organs for donation is set to revolutionise the transplant system – and it could help save lives and tens of millions of pounds.

The National Institute for Health and Care Research (NIHR) is contributing more than £1 million in funding to develop the new technology, which is known as Organ Quality Assessment (OrQA). It works in the same way as Artificial Intelligence-based facial recognition to evaluate the quality of an organ.

It is estimated the technology could result in up to 200 more patients receiving kidney transplants and 100 more receiving liver transplants a year in the UK.

Colin Wilson, transplant surgeon at Newcastle upon Tyne Hospitals NHS Foundation Trust and co-lead of the project, said: “Transplantation is the best treatment for patients with organ failure, but unfortunately some organs can’t be used due to concerns they won’t function properly once transplanted.

“The software we have developed ‘scores’ the quality of the organ and aims to support surgeons to assess if the organ is healthy enough to be transplanted.  “Our ultimate hope is that OrQA will result in more patients receiving life-saving transplants and enable them to lead healthier, longer lives.”

Professor Hassan Ugail, director of the Centre for Visual Computing at the University of Bradford, whose team is working on image analysis as part of the research, said: “Currently, when an organ becomes available, it is assessed by a surgical team by sight, which means, occasionally, organs will be deemed not suitable for transplant.

“We are developing a deep machine learning algorithm which will be trained using thousands of images of human organs to assess images of donor organs more effectively than what the human eye can see. “This will ultimately mean a surgeon could take a photo of the donated organ, upload it to OrQA and get an immediate answer as to how best to use the donated organ.”

There are currently nearly 7,000 patients awaiting organ transplant in the UK. An organ can only survive out of the body for a limited time. In most cases, only one journey from the donor hospital to the recipient hospital is possible. This means it is essential that the right decision is made quickly.

The project is being supported by NHS Blood and Transplant (NHSBT), Quality in Organ Donation biobank and an NIHR Blood and Transplant Research Unit to deliver research for the NHS. It also involves academics from the Universities of Oxford and New South Wales.?

Professor Derek Manas, medical director of NHSBT Organ Donation and Transplantation, said: “This is an exciting development in technological infrastructure that, once validated, will enable surgeons and transplant clinicians to make more informed decisions about organ usage and help to close the gap between those patients waiting for and those receiving lifesaving organs. We at NHSBT are extremely committed to making this exciting venture a success.”

Health Minister Neil O’Brien said: “Technology has the ability to revolutionise the way we care for people and this cutting edge technology will improve organ transplant services. Developed here in the UK, this pioneering new method could save hundreds of lives and ensure the best use of donated organs.

“I encourage everyone to register their organ donation decision. Share it with your family so your loved ones can follow your wishes and hopefully save others.”

Chief executive of the NIHR Professor, Lucy Chappell, said: “Funded by our Invention for Innovation Program, this deep machine learning algorithm aims to increase the number of liver and kidney donor organs suitable for transplantation. This is another example of how AI can enhance our healthcare system and make it more efficient. Once clinically validated and tested, cutting edge technology such as this holds the real promise of saving and improving lives.”

‘Proof of concept’ work has been carried out in liver, kidney and pancreas transplantation as well as at an advanced stage of pre-clinical testing in liver and kidney. ... '

Wave of Stealthy China Cyberattacks Hits U.S., Private Networks, Google Says

 Wave of Stealthy China Cyberattacks Hits U.S., Private Networks, Google Says

By The Wall Street Journal, March 22, 2023

China has routinely denied hacking into businesses or governments in other countries.

Said Charles Carmakal, Mandiant’s chief technology officer, “There is a lot of intrusion activity going undetected. We think the problem is a lot bigger than we know today.”

Researchers in Google's Mandiant division found that state-sponsored hackers in China have been using techniques that allow them to evade common cybersecurity tools and spy on government and business networks for years without being detected.

The researchers said hackers are compromising devices on the edge of the network and targeting software from VMware Inc. or Citrix Systems Inc., among others, which often run on computers without antivirus or endpoint detection software.

Mandiant's Charles Carmakal said the attacks, which generally exploit previously undetected flaws, likely are more widespread than previously known.

Carmakal noted this cyberattack method "is a lot harder for us to investigate, and it is certainly exponentially harder for victims to discover these intrusions on their own. Even with our hunting techniques, it's hard for them to find it."

From The Wall Street Journal

View Full Article - 

Persistent Computing and Virtual Worlds

 Worked a number of virtual world projects, never considered them persistent computing.  Useful thought.

Yu Yuan on Building A Persistent Virtual World The IEEE Standards Association president discusses technology for the metaverse  by EDD GENT

Despite tech giants including Meta, Microsoft, and Nvidia investing billions of dollars in the development of the metaverse, it is still little more than a fantasy. Making it a reality is likely to require breakthroughs in a range of sectors such as storage, modeling, and communication.

To spur progress in the advancement of those technologies, the IEEE Standards Association has launched the Persistent Computing for Metaverse initiative. As part of the IEEE’s Industry Connections Program, it will bring together experts from both industry and academia to help map out the innovations that will be needed to make the metaverse a reality.

Although disparate virtual-reality experiences exist today, the metaverse represents a vision of an interconnected and always-on virtual world that can host thousands, if not millions, of people simultaneously. The ultimate goal is for the virtual world to become so realistic that it is almost indistinguishable from the real one.

Today’s technology is a long way from making that possible, says Yu Yuan, president of the IEEE Standards Association. The Institute spoke with Yuan to find out more about the initiative and the key challenges that need to be overcome. His answers have been edited for clarity.

The Institute: What is persistent computing?

Yu Yuan: I have been working in virtual reality and multimedia for more than 20 years, I just didn’t call my work metaverse. After metaverse became a buzzword, I asked myself, ‘What’s the difference between metaverse and VR?’ My answer is: persistence, or the ability to leave traces in a virtual world.

Persistent computing refers to the combination of all the technologies needed to support the development and operation of a persistent virtual world. In other words, a metaverse. There are different kinds of VR experiences, but many of them are one-time events. Similar to how video games work, every time a user logs in, the entire virtual world resets. But users in the metaverse can leave traces. For example, they can permanently change the virtual world by destroying a wall or building a new house. Those changes have to be long-lasting so there will be a meaningful virtual society or meaningful economy in that virtual world.

What are the key components that are required to make persistent computing possible?

Yuan: The first is storage. In most of today’s video games, users can destroy a building, only for it to be restored the next time the user logs in to the game. But in a persistent virtual world the current status of the virtual world needs to be stored constantly. Users can create or destroy something in that world and the next time they log in, those changes will still be there. These kinds of things have to be properly stored—which means a very large amount of data needs to be stored.   ... ' 

Bard is Out and Being Tested in Changed World of High Expectations

 Google has announced their model, has been getting some criticism.  But as they say it is still just a  test.  There are lots of models jumping out there.    Google seems to have moved early without enough testing.    Expectations are high.  Also,  it competes directly with very profitable Google Search. Use directly with caution.

Try Bard and share your feedback

Mar 21, 2023  in the Google Blog.

We’re starting to open access to Bard, an early experiment that lets you collaborate with generative AI. We're beginning with the U.S. and the U.K., and will expand to more countries and languages over time.

SissieHsiao.png, Sissie Hsiao, VP, Product

Eli Collins, VP, Research

Animation of text: “Meet Bard, an early experiment by Google.” Followed by sentences explaining what Bard can do, like draft a packing list for a fishing and camping trip.

Today we’re starting to open access to Bard, an early experiment that lets you collaborate with generative AI. This follows our announcements from last week as we continue to bring helpful AI experiences to people, businesses and communities.

You can use Bard to boost your productivity, accelerate your ideas and fuel your curiosity. You might ask Bard to give you tips to reach your goal of reading more books this year, explain quantum physics in simple terms or spark your creativity by outlining a blog post. We’ve learned a lot so far by testing Bard, and the next critical step in improving it is to get feedback from more people.

Bard can help you brainstorm some ways to read more books this year.

About Bard

Bard is powered by a research large language model (LLM), specifically a lightweight and optimized version of LaMDA, and will be updated with newer, more capable models over time. It’s grounded in Google's understanding of quality information. You can think of an LLM as a prediction engine. When given a prompt, it generates a response by selecting, one word at a time, from words that are likely to come next. Picking the most probable choice every time wouldn’t lead to very creative responses, so there’s some flexibility factored in. We continue to see that the more people use them, the better LLMs get at predicting what responses might be helpful.

While LLMs are an exciting technology, they’re not without their faults. For instance, because they learn from a wide range of information that reflects real-world biases and stereotypes, those sometimes show up in their outputs. And they can provide inaccurate, misleading or false information while presenting it confidently. For example, when asked to share a couple suggestions for easy indoor plants, Bard convincingly presented ideas…but it got some things wrong, like the scientific name for the ZZ plant.  .... ' 

AI Voice Scan

Vocal scams commonly used.

AI Voice Scam, an example of some of the dangers involved.  

They Thought Loved Ones Were Calling for Help. It Was an AI Scam  By The Washington Post, March 14, 2023

In 2022, impostor scams were the second-most-popular racket in America, according to data from the Federal Trade Commission.

Technology is making it easier and cheaper for bad actors to mimic voices, convincing people, often the elderly, that their loved ones are in distress.

Credit: Elena Lacey/The Washington Post

More sophisticated artificial intelligence (AI) tools are being used to replicate a person's voice.

Fraudsters increasingly are using such tools for impostor scams, which often target the elderly, making them believe loved ones are in trouble and in need of quick cash.

University of California, Berkeley's Hany Farid said AI voice-generating software can recreate the pitch, timbre, and individual sounds of a person's voice using a short audio sample.

Said Farid, "If you have a Facebook page ... or if you've recorded a TikTok and your voice is in there for 30 seconds, people can clone your voice."

Software from the startup ElevenLabs, for example, allows users to turn a short audio sample into a synthetically generated voice using a text-to-speech tool. The software is free or costs $5 to $330 per month, depending on the amount of audio generated.

From The Washington Post

View Full Article - May Require Paid Subscription  

GitHub unveils Copilot X: The Future of AI-powered Software Development

Now here is a future that has some real value ... 

GitHub unveils Copilot X: The future of AI-powered software development

Michael Nuñez in Venturebeat

@MichaelFNunez, March 22, 2023

Join top executives in San Francisco on July 11-12, to hear how leaders are integrating and optimizing AI investments for success. Learn More

GitHub, the leading platform for software development collaboration, has announced today the next step in AI-driven software development with the introduction of Copilot X. As a pioneer in the use of generative AI for code completion, GitHub is now taking its partnership with OpenAI further by adopting the latest GPT-4 model and expanding Copilot’s capabilities.

Launched less than two years ago, GitHub Copilot has already made a significant impact on the world of software development. GitHub reported today that the AI-powered tool, built using OpenAI’s Codex model, currently writes 46% of the code on the platform and has helped developers code up to 55% faster. By auto-completing comments and code, Copilot serves as an AI pair programmer that keeps developers focused and productive.

GitHub Copilot X, the upgraded version being released today, represents a bold vision for the future of AI-powered software development. With an emphasis on accessibility, the upgraded Copilot will now be available throughout the entire development life cycle, going beyond mere code completion. By incorporating chat and voice features, developers can communicate with Copilot more naturally. Additionally, Copilot X will be integrated into pull requests, command lines and documentation, providing instant answers to questions about projects.

The transformative potential of AI in software development is on full display with GitHub Copilot X. By reducing boilerplate and manual tasks, developers can focus on more complex and innovative work. This new level of productivity will allow developers to concentrate on the bigger picture, fostering innovation and accelerating human progress.  ... ' 

Large language models also Work for Protein Structures

We asked this question long ago, usefully answered?  Very big deal if so.

THE LANGUAGE OF BIOCHEMISTRY —

Large language models also work for protein structures

Training on raw protein sequences allows the AI to make inferences about structure.

JOHN TIMMER - 3/16/2023, 3:01 PM

The success of ChatGPT and its competitors is based on what's termed emergent behaviors. These systems, called large language models (LLMs), weren't trained to output natural-sounding language (or effective malware); they were simply tasked with tracking the statistics of word usage. But, given a large enough training set of language samples and a sufficiently complex neural network, their training resulted in an internal representation that "understood" English usage and a large compendium of facts. Their complex behavior emerged from a far simpler training.

A team at Meta has now reasoned that this sort of emergent understanding shouldn't be limited to languages. So it has trained an LLM on the statistics of the appearance of amino acids within proteins and used the system's internal representation of what it learned to extract information about the structure of those proteins. The result is not quite as good as the best competing AI systems for predicting protein structures, but it's considerably faster and still getting better.  

LLMs: Not just for language

The first thing you need to know to understand this work is that, while the term "language" in the name "LLM" refers to their original development for language processing tasks, they can potentially be used for a variety of purposes. So, while language processing is a common use case for LLMs, these models have other capabilities as well. In fact, the term "Large" is far more informative, in that all LLMs have a large number of nodes—the "neurons" in a neural network—and an even larger number of values that describe the weights of the connections among those nodes. While they were first developed to process language, they can potentially be used for a variety of tasks. .... ' 

UK Says AI is Getting Very Important

In part pushed by recent advances?

AI News

Editorial: UK puts AI at the centre of its Budget

By Ryan Daws | March 16, 2023 | TechForge Media

Categories: Artificial Intelligence, Development, Enterprise, Industries, Legislation & Government, Machine Learning, Quantum Computing,

Ryan is a senior editor at TechForge Media with over a decade of experience covering the latest technology and interviewing leading industry figures. He can often be sighted at tech conferences with a strong coffee in one hand and a laptop in the other. If it's geeky, he’s probably into it. Find him on Twitter (@Gadget_Ry) or Mastodon (@gadgetry@techhub.social)

British Chancellor Jeremy Hunt announced the country’s Spring Budget this week and supporting the AI industry was at the centre.

The UK is Europe’s AI leader. Indeed, behind the US and China, the country’s tech sector overall has the third-highest amount of VC investment in the world – more than Germany and France combined – and has produced more than double the number of $1 billion tech firms than any other European country.

Gerard Grech, CEO of Tech Nation, said:

“As a nation uniquely positioned between two economic powerhouses, the US and the EU, we must harness innovative regulation that will enable us to propel ourselves as an international hub and leader for AI, quantum computing, and deep tech.

This is a critical step towards creating a distinctive, value-driven tech ecosystem in the UK, setting us apart from other tech hubs.”

To support British startups, an ‘AI Sandbox’ was announced by the chancellor. The sandbox features a number of initiatives designed to encourage AI research and investment.

Among them is a prize pot containing millions of pounds. £1 million will be up for grabs every year over the next decade for the best AI innovations created by teams and individuals.

Ludovico Lugnani, Technology Solicitor at BDB Pitmans, comments:

“Following yesterday’s news of Open AI’s launch of its upgraded GPT-4 chatbot, the Budget’s announcement as to the creation of an AI sandbox offers a promising outlook for the UK to speed up the arrival of AI products to market.

As part of this, particular emphasis should be placed on providing effective guidance as to the implications of copyright law on generative AI applications following the recent claim by Getty Images against Stability AI over breach of copyright.”

Elsewhere, £2.5 billion is being ploughed into advancing quantum computing. The powerful machines will enable a literal “quantum leap” in AI.

“The power that AI’s complex algorithms need can be provided by quantum computing,” the chancellor told the Commons.

£900 million is also being invested to create an exascale supercomputer that will be several times more powerful than the country’s biggest computers and advance not just AI research, but also science, healthcare, defense, weather modelling, and more.

“[The supercomputer] should be a huge boost to the UK’s ability to support cutting-edge research in areas requiring complex modelling and simulations, such as climate change, pharmaceutical development and hi-tech engineering,” commented Nick White, Partner at law firm Charles Russell Speechlys.

Only one exacomputer is currently known to exist. The computer, known as Frontier, is housed at the Oak Ridge National Laboratory in Tennessee, United States.

Other relevant announcements in the Spring Budget are targeted less at the AI industry specifically but aim to solidify the UK’s ranking as the second-best country after the US to invest and launch a business.

Under the ‘Full Expensing’ plans, companies investing in R&D and IT equipment to boost growth will benefit. Every pound a company spends on new IT equipment and machinery can be deducted in full from taxable profits.  .... '

Replacing Coders Already?

Inevitable.... 

Startups Are Already Using GPT-4 to Spend Less on Human Coders

GPT-4 "saves a lot of time and a lot of money, obviously, because we haven't had to hire additional resources."   By Chloe Xiang, March 20, 2023, 9:00am

1674655888922-screen-shot-2023-01-25-at-91114-am

SCREENSHOT FROM OPENAI WEBSITE 

Since GPT-4 was released last week, many users have noticed its advanced coding abilities. GPT-4, OpenAI’s latest version of the large language model that ChatGPT is built on, has been able to code games like Pong and make simple apps after being given prompts written in conversational English. Naturally, this has led to widespread fear from a number of computer science students and software developers who are afraid that their jobs will soon be rendered obsolete by AI. ....' 

Google Bard

 Got into Google Bard from the wait list in just a few hours.  See Bard.google.com    Here is how they describe it.   And Perhaps naturally, each interaction also includes the ability to use a google search .  Says it uses the Web as a source of knowledge, as well as books, articles, other accessible resources.  

Bard.google.com

Google Bard is Google's experimental, conversational, AI chat service. It is meant to function similarly to ChatGPT, with the biggest difference being that Google's service will pull its information from the web.

Google Bard was named after the Bards of Celtic cultures, who were professional story-tellers, musicians, and oral historians. Google Bard is designed to be a modern-day equivalent, using artificial intelligence to generate creative text formats of text content, like poems, code, scripts, musical pieces, email, letters, etc.

Google Bard is still under development, but it has learned to perform many kinds of tasks, including:

- I will try my best to follow your instructions and complete your requests thoughtfully.

- I will use my knowledge to answer your questions in a comprehensive and informative way, even if they are open ended, challenging, or strange.

- I will generate different creative text formats of text content, like poems, code, scripts, musical pieces, email, letters, etc. I will try my best to fulfill all your requirements ....

Seems well done, does seem to allow for some stranger questions.    They warn you its new and still a work in progress, experimental, can make mistakes, etc.   It seems now most every one wants such a capability added to their world of tools. 

More Fears of Tok

TikTok: UK ministers banned from using Chinese-owned app on government phones

TikTok on a phone, By Chas Geiger & Zoe Kleinman, BBC News

British government ministers have been banned from using Chinese-owned social media app TikTok on their work phones and devices on security grounds.

The government fears sensitive data held on official phones could be accessed by the Chinese government.

Cabinet Minister Oliver Dowden said the ban was a "precautionary" move but would come into effect immediately.

TikTok has strongly denied allegations that it hands users' data to the Chinese government.

Theo Bertram, the app's vice-president of government relations and public policy in Europe, told the BBC it believed the decision was based on "more on geopolitics than anything else".

"We asked to be judged not on the fears that people have, but on the facts," he added.

The Chinese embassy in London said the move was motivated by politics "rather than facts" and would "undermine the confidence of the international community in the UK's business environment".

Mr Dowden said he would not advise the public against using TikTok, but they should always "consider each social media platform's data policies before downloading and using them".

Prime Minister Rishi Sunak had been under pressure from senior MPs to follow the US and the European Union in barring the video-sharing app from official government devices.

But government departments - and individual ministers - have embraced TikTok as a way of getting their message out to younger people.

Use of the app has exploded in recent years, with 3.5 billion downloads worldwide.

Its success comes from how easy it is to record short videos with music and fun filters, but also from its algorithm which is good at serving up videos which appeal to individual users.

It is able to do this because it gathers a lot of information on users - including their age, location, device and even their typing rhythms - while its cookies track their activity elsewhere on the internet.

US-based social media sites also do this but TikTok's Chinese parent company ByteDance has faced claims of being influenced by Beijing.   ... ;

Robot Security Guards

Inevitable, increasing in smart application.

Robots are your new office security guard      in Axios

Jennifer A. Kingson

See Cobalt Robotics.

They stand five feet tall and glide at three miles per hour, patrolling office buildings for everything from broken fire alarms to suspicious activity: Security robots are starting to replace human guards in workplaces and beyond.

Why it matters: Despite some hiccups, robots armed with sensors and artificial intelligence are making inroads in diverse fields — from window washing and pizza making to bartending and caring for the elderly.

Driving the news: Lower costs mean it's now substantially cheaper for companies to use robots than traditional guards for 24/7 security.

Robots can check in visitors and issue badges, respond to alarms, report incidents, and see things security cameras can't.

Security robots don't get bored, tired, or distracted by their phones — and it's safer for them to confront intruders and other hazards.

Two-way communications systems allow employees to report problems or request human help by talking to the robot.

By the numbers: Using a robot guard vs. a human can save a company $79,000 per year, according to a recent report by Forrester Research.

What they're saying: "All this money has really poured into service robotics because of the money that has gone into autonomous vehicles," says Mike LeBlanc, president and COO of Cobalt Robotics, which is leading the charge to populate offices with non-human security guards.

Two views of a Cobalt Robotics robot in the office, showing how it roams hallways and has an interactive tablet that allows people to communicate with a call center.

At left, a Cobalt Robotics unit prowls hallways to scout for problems and allows people to report concerns. At right, an employee uses the robot's tablet to communicate with a specialist at a remote call center. Photos courtesy of Cobalt Robotics.

How it works: Cobalt's robots are built to the specifications of a particular building's ramps and elevators.   They roam hallways looking for possible problems — like unusual motion at night or a door that's been propped open — and report back to a human-staffed call center.

"They have fabric, so they're designed to look like a piece of high-end office furniture," LeBlanc tells Axios. "And they have a tablet on the front that allows people to interact with our 24/7 specialists at any given time."

"People can tap on the screen of the robot, a person will come up on the screen, and they'll be able to ask them what's going on," LeBlanc said. "They can say, 'There's a leak or spill over here,' or 'There's someone in the office who's making me uncomfortable.'"

Case study: Food delivery startup DoorDash is using Cobalt robots across its corporate sites, for everything from COVID-19 temperature checks to routine security patrols, alarm responses, and security escort services. ...  

Humans get X-Ray Vision in Augmented Reality

 Seen this in previous worlds we experimented with.   Concept interesting. 

MIT researchers invented an augmented reality headset that gives humans X-ray vision. The invention, dubbed X-AR, combines wireless sensing with computer vision to enable users to see hidden items. X-AR can help users find missing items and guide them toward these items for retrieval. This new technology has many applications in retail, warehousing, manufacturing, smart homes, and more.

For more information, check out:

Website: https://Xar.media.mit.edu

Paper: https://www.mit.edu/~fadel/papers/XAR-paper.pdf

Instagram: @mit_sk_lab (https://instagram.com/mit_sk_lab?igshid=YmMyMTA2M2Y=)

Authors: Tara Boroushaki, Maisy Lam, Laura Dodds, Aline Eid, Fadel Adib

Video Production: Maisy Lam, Jimmy Day

UI design: Maisy Lam, Yuechen Wang

Funding: NSF, Sloan Foundation, MIT Media Lab  .... 

Startups Using GPT-4

GPT-4is impressive so far ....

Startups Are Already Using GPT-4 to Spend Less on Human Coders

GPT-4 "saves a lot of time and a lot of money, obviously, because we haven't had to hire additional resources."

By Chloe Xiang  in Vice.com

March 20, 2023, 9:00am

Since GPT-4 was released last week, many users have noticed its advanced coding abilities. GPT-4, OpenAI’s latest version of the large language model that ChatGPT is built on, has been able to code games like Pong and make simple apps after being given prompts written in conversational English. Naturally, this has led to widespread fear from a number of computer science students and software developers who are afraid that their jobs will soon be rendered obsolete by AI.    ... '

Google's Bard Is Here (Waitlist)

Yet another chatty AI,   examining.  From the Lamda Language model.

-  You can sign up to try Bard at bard.google.com. We'll begin rolling out access in the U.S. and U.K. today and expanding over time to more countries and languages. Until next time, Bard out! -

I am now on the waitlist, more will follow here.

Bard: Google's rival to ChatGPT launches for over-18s

The Bard chatbot answering questions

By Zoe Kleinman, Technology editor

Google will begin rolling out its AI chatbot Bard today, but it will only be available to certain users and they will have to be over the age of 18.

Unlike its viral rival ChatGPT, it can access up-to-date information from the internet and has a "Google it" button which accesses search.

It also namechecks its sources for facts, such as Wikipedia.

But Google warned Bard would have "limitations" and said it might share misinformation and display bias.

This is because it "learns" from real-world information, in which those biases currently exist - meaning it is possible for stereotypes and false information to show up in its responses.

How do chatbots work?

AI chatbots are programmed to answer questions online using natural, human-like language.

They can write anything from speeches and marketing copy to computer code and student essays.

When ChatGPT launched in November 2022, it had more than one million users within a week, said OpenAI, the firm behind it.

Microsoft has invested billions of dollars in it, incorporating the product into its search engine Bing last month.

It has also unveiled plans to bring a version of the tech to its office apps including Word, Excel and Powerpoint.

Google has been a slower and more cautious runner in the generative AI race with its version, Bard, which launches in the US and UK to begin with. Users will have to register to try it out.

Bard is a descendant of an earlier language model of Google's called Lamda, which was never fully released to the public. It did, however, attract a lot of attention when one of the engineers who worked on it claimed its answers were so compelling that he believed it was sentient. Google denied the claims and he was fired.

Digital Twins in Consumer Package Goods

 In the process of looking for in process applications 

Digital Twins & CPG Manufacturing Transformation

By Justin Honaman, Worldwide Head of Consumer Products – Food & Beverage, AWS

Good intro piece

dig·​i·​tal: of, relating to, or utilizing devices constructed or working by the methods or principles of electronics; [1]also: characterized by electronic and especially computerized technology; : composed of data in the form of especially binary digits

/twin/: something containing or consisting of two matching or corresponding parts.

For the last few years, the term Digital Twin has been at the top of the buzzword list for manufacturers and industrial companies, often meaning different things in different production environments. Most of these organizations have developed Digital Twins to improve operations and product offerings and deliver more business value to their end customers. The concept of digital twins is not new and dates back to the early days of the space program. The Apollo 13 mission in the 1960s is an early use case of using twins to model the state of the damaged spacecraft and bring the astronaut crew safely back to Earth.

In recent years, the core ideas of Digital Twin have been commonly attributed to Michael Grieves of the Digital Twin Institute, who developed the concept throughout the 2000s, and NASA’s John Vickers, who coined the term Digital Twin in 2010. Customers today are seeking to deploy Digital Twins across a broad range of applications, including the design of complex equipment, manufacturing operations, preventive maintenance, precision medicine, digital agriculture, city planning, 3D immersive environments, and most recently, metaverse-type applications.

Digital Twin is often applied broadly to describe any virtual model, including engineering simulations, CAD models, IoT dashboards, or gaming environments. Digital Twins are more than just a marketing term, but rather a new technology that has only become feasible in the past few years with the convergence of at-scale computing, modeling methods, and IoT connectivity.

Let’s first define Digital Twin and how to integrate existing modeling methods into Digital Twins.

What Is a Digital Twin?

A Digital Twin is a living digital representation of an individual physical system that is dynamically updated with data to mimic the true structure, state, and behavior of the physical system, to drive business outcomes.  .... (much more at the link) 

BBC advises staff to delete TikTok from work phones

Security addressed  at the BBC

BBC advises staff to delete TikTok from work phones

Published, 22 hours ago, By Zoe Kleinman, Andre Rhoden-Paul & Chris Vallance

BBC News

The BBC has advised staff to delete TikTok from corporate phones because of privacy and security fears.

The BBC seems to be the first UK media organisation to issue the guidance - and only the second in the world after Denmark's public service broadcaster.

The BBC said it would continue to use the platform for editorial and marketing purposes for now. TikTok has consistently denied any wrongdoing.   The app has been banned on government phones in the UK and elsewhere.

Countries imposing bans include the US, Canada, New Zealand and Belgium, while the same applies to anyone working at the European Commission.

However, it is still permitted on personal devices.

The big fear is that data harvested by the platform from corporate phones could be shared with the Chinese government by TikTok's parent company ByteDance, because its headquarters are in Beijing.

TikTok says the bans are based on "fundamental misconceptions".

ByteDance employees were found to have tracked the locations of a handful of Western journalists in 2022. The company says they were fired.  Alicia Kearns, who chairs the Foreign Affairs Committee, was asked for her view on the BBC's decision, and tweeted: "If protecting sources isn't a priority, that's a major problem."

'Encouraging TikTok, not banning it'

Dominic Ponsford, editor-in-chief of journalism industry trade publication the Press Gazette, said it would be interesting to see what other media organisations decide to do.

He told the BBC: "I suspect everyone's chief technical officer will be looking at this very closely.

"Until now, news organisations have been very keen to use TikTok, because it's been one of the fastest-growing social media platforms for news publishers over the last year, and it's been a good source of audience and traffic.

"So most of the talk in the news media has been around encouraging TikTok rather than banning it."

BBC taking security 'incredibly seriously'

The short-video platform is known for its viral dance crazes, sketches and filters and is hugely popular among young people, with more than 3.5 billion downloads worldwide.  Channel 4 News presenter Krishnan Guru-Murthy tweeted in reaction to the decision: "BBC News making big play for views on TikTok but now the BBC is telling staff not to have it on their phones".

A BBC spokesperson said it took the safety and security of its systems, data and people "incredibly seriously".

TikTok banned from official UK government phones

How much data does TikTok collect?.... '