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Scientists closer to solving mysteries of universe after measuring gravity in quantum world – University of Southampton

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Published:26February2024

Scientists are a step closer to unravelling the mysterious forces of the universe after working out how to measure gravity on a microscopic level.

Experts have never fully understood how the force which was discovered by Isaac Newton works in the tiny quantum world.

Even Einstein was baffled by quantum gravity and, in his theory of general relativity, said there is no realistic experiment which could show a quantum version of gravity.

But now physicists at the University of Southampton, working with scientists in Europe, have successfully detected a weak gravitational pull on a tiny particle using a new technique.

They claim it could pave the way to finding the elusive quantum gravity theory.

The experiment, published in the Science Advances journal, used levitating magnets to detect gravity on microscopic particles small enough to boarder on the quantum realm.

Lead author Tim Fuchs, from the University of Southampton, said the results could help experts find the missing puzzle piece in our picture of reality.

He added: For a century, scientists have tried and failed to understand how gravity and quantum mechanics work together.

Now we have successfully measured gravitational signals at a smallest mass ever recorded, it means we are one step closer to finally realising how it works in tandem.

From here we will start scaling the source down using this technique until we reach the quantum world on both sides.

By understanding quantum gravity, we could solve some of the mysteries of our universe like how it began, what happens inside black holes, or uniting all forces into one big theory.

The rules of the quantum realm are still not fully understood by science but it is believed that particles and forces at a microscopic scale interact differently than regular-sized objects.

Academics from Southampton conducted the experiment with scientists at Leiden University in the Netherlands and the Institute for Photonics and Nanotechnologies in Italy, with funding from the EU Horizon Europe EIC Pathfinder grant (QuCoM).

Their study used a sophisticated setup involving superconducting devices, known as traps, with magnetic fields, sensitive detectors and advanced vibration isolation.

It measured a weak pull, just 30aN, on a tiny particle 0.43mg in size by levitating it in freezing temperatures a hundredth of a degree above absolute zero about minus-273 degrees Celsius.

The results open the door for future experiments between even smaller objects and forces, said Professor of Physics Hendrik Ulbrichtalso at the University of Southampton.

He added: We are pushing the boundaries of science that could lead to new discoveries about gravity and the quantum world.

Our new technique that uses extremely cold temperatures and devices to isolate vibration of the particle will likely prove the way forward for measuring quantum gravity.

Unravelling these mysteries will help us unlock more secrets about the universe's very fabric, from the tiniest particles to the grandest cosmic structures.

Read the study at doi.org/10.1126/sciadv.adk2949.

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Breakthrough in Quantum Measurement of Gravity Achieved Using Levitating Magnets – The Debrief

Physicists are one step closer to the measurement of gravity at the quantum level, according to a team whose recent studies move us closer to understanding some of the most mysterious forces at work in our universe.

Gravity is the fundamental interaction that produces attraction between all the objects possessing mass in our universe. Although the weakest of the four fundamental interactions recognized by physicists, it is the one that most of us are familiar with, as we experience the effects of gravity virtually every moment of our lives.

However, due to its weakness, gravity has no significant influence when it comes to subatomic particles, and experts have long questioned how it works in the quantum realma conundrum that even baffled Albert Einstein, whose theory of general relativity argued that there are no experiments that could demonstrate a quantum version of gravity.

That is until now, as an international team of physicists says they have succeeded in developing a novel technique that allowed them to detect a weak gravitational pull on a microscopic particle, an achievement which they say may advance our progress toward unraveling a long-sought theory of quantum gravity.

In their experiment, the physicists were able to detect gravity on tiny particles near the boundaries of the quantum realm by employing superconducting devices called traps. During their experiment, they measured a weak pull from a microscopic particle by levitating it under extreme freezing conditions approaching absolute zero.

University of Southampton physicist Tim Fuchs said the achievement could help move us toward understanding our universe by revealing a missing puzzle piece in our current picture of reality.

For a century, scientists have tried and failed to understand how gravity and quantum mechanics work together, Fuchs said in a statement.

Now we have successfully measured gravitational signals at [the] smallest mass ever recorded, it means we are one step closer to finally realizing how it works in tandem, he added.

Fuchs said that his teams next objective is to attempt to reduce the scale of the source using the new technique so that it can be applied to the quantum world on both sides. This could help scientists to unravel some of the most pressing mysteries about our universe, including its origins, and whether there is indeed a grand theory that unites all the known forces.

Presently, quantum phenomena are still mysterious to physicists like Fuchs, since the behavior of particles at the microscopic scale is vastly different from how matter behaves at the normal scale we experience in our daily lives.

However, the new findings could enable future experiments involving even smaller objects.

Our new technique that uses extremely cold temperatures and devices to isolate vibration of the particle will likely prove the way forward for measuring quantum gravity, said Hendrik Ulbricht, a Professor of Physics at the University of Southampton.

Unravelling these mysteries will help us unlock more secrets about the universes very fabric, from the tiniest particles to the grandest cosmic structures.

The teams new study, Measuring gravity with milligram levitated masses, appeared in the February 23, 2024 edition of Science Advances.

Micah Hanks is the Editor-in-Chief and Co-Founder of The Debrief. He can be reached by email atmicah@thedebrief.org. Follow his work atmicahhanks.comand on X:@MicahHanks.

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New study finds AEC firms using 50% more cloud storage than before – Planning, Building & Construction Today

The 2024 AEC Data Insights Report from Egnyte shows that the Architecture, Engineering, and Construction (AEC) industry is embracing the shift to cloud storage and other digital construction tools.

The data storage requirements of the companies surveyed grew at an average compounded annual growth rate of 50.3%.

Egynte observes that this rapid growth trend began during the pandemic, but as companies started to see the benefits of the cloud, growth has maintained that pace.

Cloud storage and collaboration solutions have become an increasingly normalised part of the AEC industry workings- and can help meet new regulatory requirements, such as those of the Cybersecurity Maturity Model Compliance (CMMC) in the United States and the Building Safety Act in the UK.

The findings are based on data from more than 4,000 companies in Egnytes customer base, which includes firms representing every stage of the AEC project lifecycle.

The insights we gleaned from this years report reflect the conversations we have with AEC firms on a daily basis. Companies are relying more heavily on digital collaboration to get the job done a trend that shows no signs of slowing down, said Ronen Vengosh, senior vice president of Industry Solutions at Egnyte.

Their increased reliance on cloud collaboration and file storage coupled with the high frequency of cybersecurity threats these firms encounter highlights the need for secure, reliable cloud collaboration solutions.

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Storage and backup spend in 2024 targets risk and resilience – ComputerWeekly.com

Storage and backup investment plans for 2024 show a significant bias towards averting risk and building resilience. At the same time, storage spending plans lean towards the cloud, but with very robust on-premise storage spending plans also present.

Those are the findings of the Technology spending intentions survey from TechTarget and ESG, which questioned 1,432 technology decision-makers worldwide over three key areas:

When asked about storage and data protection technologies that organisations plan to invest in over the next 12 months, the overwhelming majority of responses indicate plans of arguably a defensive nature. Therefore, at number one, we find data governance, risk and compliance, with disaster recovery, cyber resilience and business continuity next. Joint-fourth is ransomware protection. Only in sixth place do we see something thats not explicitly about protection of data or risk, namely public cloud file storage as a key investment.

Next up, we were back on defence, with data management of cloud and unstructured data, backup for cloud data, and backup hardware and software.

Public cloud object storage comes last in the list of 10 investment priorities.

When these responses were broken down between enterprise and mid-market decision-makers, storage-as-a-service also creeps into the top 10 priorities.

Public cloud storage (file and object) continues to be the most likely storage investment. But on-premise investments are still significant, especially in the context of organisations reevaluating whether the cloud is the right place to store data and applications.

As mentioned above, when it comes to investment in storage capacity, cloud storage is a prominent priority, with file (31% of those questioned) and object (24%) the most significant storage investments planned worldwide.

Storage as a service came in third in the list of investment priorities, with planned spend in 2024 by 23% of respondents.

Cloud block storage was also cited by 16% of those asked, but the other seven in a list of 11 storage technology areas are unambiguously on-premise.

Internal server storage tops the list of investment priorities here (19%), followed by hyper-converged infrastructure (16%), software-defined storage (15%) and on-premise SAN capacity Ethernet (15%) and Fibre Channel (12%). Behind those are flash storage (12%) and on-premise direct attached storage (10%).

The survey also broke down responses between North America, EMEA and Asia-Pacific. Where these vary significantly includes public cloud file and object storage in North America, which lags behind the worldwide average (26% and 19%), while it leads in cloud block storage plans by a long way (29% versus 16%).

Meanwhile, flash storage plans are significantly more prevalent in North America (16%) and APAC (14%) than in EMEA (9%).

In data protection generally, theres a big bias towards building resilience and averting risk. Meanwhile, the nuts and bolts of that resilience, in the shape of backup including of cloud data such as containers takes up a significant portion of planned spend in 2024.

Priorities around data protection are topped by disaster recovery (37%), with the closely allied business continuity in third place (32%).

All of the top five priorities centre on resilience and include data governance, risk and compliance in joint top (37%), and cyber resilience services (33%).

Backup figures heavily as a spending priority, with backup for cloud data such as VMs and containers the most prominent (25%), backup hardware and software generally (24%), and backup-as-a-service (18%), endpoint backup (17%), and SaaS application data backup also on 17%.

In the middle of all of the above is data management for example, for cloud and unstructured data of which 27% said it would be an investment priority in 2024.

Archiving is among investment plans for 17% of those questioned.

Meanwhile, tapes not dead, but its not a huge priority for many (3%), and is down on last years 6%.

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Reducing Cloud Waste a Top Priority in 2024, FinOps Foundation Says – Datanami

(ESB-Professional/Shutterstock)

The increasing cost of cloud computing, particularly when it comes to storing data to feed AI algorithms, is a growing concern among companies, particularly larger ones, according to a new report by the FinOps Foundation.

The FinOps Foundations fourth annual State of FinOps Survey, released last week, detected some significant changes in cloud spending patterns compared to previous years. The survey found that spending on compute capacity is no longer the big issue that it once was, and that compute is now the most optimized among the different categories of cloud spending.

Now, spending on cloud storage, databases, and containers are the main points of concern, according to the survey by FinOps Foundation, which touched more than 1,200 IT practitioners across more than 1,000 companies, with an average cloud bill of $44 million per year and total combined spending of $55 billion annually.

Reducing waste is the key FinOps priority for 2024 (Courtesy: FinOps Foundation under the CC BY 4.0)

The biggest FinOps spending is targeting compute instances, the survey shows, with more than 50% having already spent heavily to optimize compute. That leaves plenty of room for optimizing other aspects of cloud computing, the FinOps Foundation says, including data and storage, database, containers, backup and retention, data transfer and networking, and more.

One area where lots of improvement can be made is in regards to forecasting of cloud spending. While the biggest companies have already made substantial investments in forecasting cloud spending, there are many ways they can enhance their forecasts through automation, optimization, and adapting to user behavior.

AI represents both a threat to FinOps, as well as a potential savior. On the one hand, AI can consume enormous demand for storage and compute in the cloud. But on the other, AI can potentially help companies to optimize their cloud spending. Currently, AI is mostly hurting, the FinOps Foundation says.

Reining in AI and machine learning spending was a bigger concern for larger companies, or those spending $100 million or more per year in the cloud, the FinOps Foundation says. Just 31% of all survey respondents said AI and ML spending was impacting their FinOps practice, whereas that percentage jumps to 45% for companies spending $100 million or more annually in the cloud.

AI, rather than initially helping, is actually starting to negatively impact cloud bills for large spenders and is directly impacting margins due to increased spending in the cloud, J.R. Storment, the FinOps Foundations executive director, stated in a press release.

What FinOps practitioners are optimizing (Image courtesy FinOps Foundation under the CC BY 4.0)

One trend to look out for in the coming years is the intersection between the FinOps and sustainability teams, the FinOps Foundation says. Today, only 20% of FinOps teams are working with sustainability teams, but 50% foresee that taking place in the future, according to the survey.

The survey shows that the field of FinOps is alive and well, writes Mike Fuller, CTO of the FinOps Foundation, which is associated with the Linux Foundation.

This years data illustrate that FinOps is not a one-and-done cost-cutting activity, Fuller writes in a blog. FinOps is about aligning spending to business goals, and since business goals must shift from time to time (as they did this year), FinOps is never done. Businesses continue to need FinOps practitioners to help shift behavior as cloud adoption hits material levels, and to maintain it when business priorities change.

You can access the State of FinOps 2024 report here.

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Waste Not, Want Not

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Ditching Google Drive for Microsoft OneDrive was one of the best choices I’ve ever made – TechRadar

Like most parents, the amount of digital photos I took exploded when my daughter was born. By the time her umbilical cord was cut Id already had emails from Google not to congratulate me (thanks Google), but to let me know my Google Drive was filling up fast.

As my daughter turned from a grey and slimy newborn into an adorable baby, and started actually doing interesting and cute things, rather than just being a screaming potato, my Google Drive capacity came under even greater strain thanks to the deluge of photos I was taking. Googles emails became more alarming as I reached my storage quota.

As a filthy Android user, Google Photos and Google Drive were my default services for cloud storage, and I hadnt felt the need to look elsewhere. As an owner of an original Google Pixel smartphone, it actually made sense to stick with Google Photos, as the company was once offering unlimited storage for your snaps. Sadly, not only had Google since stopped offering that incentive to get people to buy its smartphones, but by the time my daughter was born, Id switched to a Samsung smartphone.

Having the photos I take on my smartphone get automatically backed up in full quality was extremely important for me these were photos I would be devastated to lose if my phone got lost or broken. So, with the threat that my photos would no longer get backed up, I needed to act fast.

The most obvious step was to increase my Google Drive storage amount. However, I was already paying $2.99 per month for 200GB. The only larger option was for 2TB for $9.99 a huge increase in the monthly price and even with my trigger-happy snapping, I didnt think I would need that much. As a new parent, I needed to watch my outgoings. So, I decided to shop about and it didnt end well for Google.

When looking for a replacement cloud storage solution for my rapidly growing photo collection, there was one service I had already made up my mind about not using OneDrive.

This was Microsofts cloud storage solution, and in classic Microsoft style, it had been pushing it hard in Windows 11. To an almost obnoxious extent. Every time I tested out a new laptop or PC which due to my job, is very often I was being begged to turn on OneDrive to sync all my devices.

I wasnt a fan, and most of the time, I had been happy with Google Drive, so I didnt want another cloud storage service and I resented constantly being asked about it.

But as I was no longer content with Google Drive, I thought Id look into what Microsoft was offering. While, like Google, Microsoft offers a free tier for OneDrive, its just 5GB, which isnt enough for my photos.

However, the Microsoft 365 Personal tier offers 1TB of storage a lot more than the 200GB I was using, but without being more than I would need for $6.99 a month (and its cheaper if you pay yearly). Along with 1TB of storage, it also includes licenses for Microsoft Word, Excel and PowerPoint. This was another big selling point for me, as even in the age of Google Docs, Im one of those weirdos who still prefers to use office apps, especially word processors, that have been installed locally.

For longer-form articles, they give me a sense of security and control I just dont feel with Google Docs, so I was thinking of investing in Microsoft Office anyway (or using the free alternative LibreOffice). Having physical files on my PC also meant I could back them up to a NAS device, while also using cloud storage (paranoid? Perhaps).

One thing I do like about Google Docs is that its constantly saving in the background, so if your PC crashes, youre unlikely to lose much work, and you can log in and access the documents from other machines as well.

Even if your PC completely breaks, your documents will be accessible via the internet from another machine. So, I was quite happy to see that Word (and the other Office applications) offer similar functionality. If you save a document to your OneDrive folder on your PC, you can select it to auto save constantly (rather than saving every five minutes or so), and then access those files via the web. It also has version history as well, and you can edit documents within a web browser, so you dont even need Word or Excel installed.

That made my mind up and I subscribed. So far Ive been very happy with OneDrive, and feel a bit bad about ignoring it for so long. Theres an Android app available that automatically uploads the photos I take on my phone, and also helps me save space on my handset by safely deleting uploaded images once they are backed up. Its not as seamless as using the Photos app and Google Drive on an Android phone, but its also not the nightmare I had feared.

So far, the 1TB of storage space has been more than enough for all my photos. I haven't felt the need (nor been bugged) to upgrade my storage. In fact, I now use OneDrive for storing music projects Ive created in Ableton Live. These can be quite large files, but I still have plenty of space, and it means I can open up those projects on my desktop PC as well as my MacBook. Yep, theres a OneDrive app for Macs, and it integrates quite nicely into macOS.

Of course, Windows 11 integration is where it shines even if I still get annoyed by Windows 11 trying to make everything default to my OneDrive storage, and having to scroll past all my OneDrive folders in File Explorer just to get to my local storage (you know, sometimes Microsoft I may want to go into my Downloads folder).

Its also helped when reviewing new Windows 11 devices. Instead of getting angry about the suggestion of signing up for OneDrive, now when I set up a new Windows 11 laptop or PC, I use my Microsoft Account and enable OneDrive and all of my files and folders appear without me having to install any third party applications.

So I am happy to admit that I was wrong about OneDrive its a genuinely useful and good value service. Perhaps if Microsoft hadnt been so pushy about me trying it, Id have given it a go sooner.

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The Florida House passes a bill requiring disclaimers on political ads with AI – WMNF

AI - artificial intelligence graphic by Black Kira via iStock for WMNF News.

2024 The News Service of Florida

Political advertisements created using generative artificial intelligence could soon require a disclaimer that makes clear the technology was involved, under a measure passed Wednesday by the Florida House.

House members voted 104-8 to approve the bill (HB 919) amid questions by some Democrats about a criminal penalty included in the measure.

Under the bill, political advertisements using images, video, audio, graphics, or other digital content that are created using artificial intelligence would have to include the following disclaimer: Created in whole or in part with the use of generative artificial intelligence (AI).

People who pay for, sponsor or approve political ads found to be in violation could face first-degree misdemeanor charges.

Bill sponsor Alex Rizo, R-Hialeah, pointed to artificial intelligence possibly being used to create misleading images or other content.

The reason why we wanted to give this (bill) a little more teeth than usual election bills or election laws have, is because now for the first time there is a real concern to really change reality on people, Rizo said.

A similar Senate bill (SB 850) is awaiting consideration by the Senate.

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We’ve been here before: AI promised humanlike machines in 1958 – The Conversation

A roomsize computer equipped with a new type of circuitry, the Perceptron, was introduced to the world in 1958 in a brief news story buried deep in The New York Times. The story cited the U.S. Navy as saying that the Perceptron would lead to machines that will be able to walk, talk, see, write, reproduce itself and be conscious of its existence.

More than six decades later, similar claims are being made about current artificial intelligence. So, whats changed in the intervening years? In some ways, not much.

The field of artificial intelligence has been running through a boom-and-bust cycle since its early days. Now, as the field is in yet another boom, many proponents of the technology seem to have forgotten the failures of the past and the reasons for them. While optimism drives progress, its worth paying attention to the history.

The Perceptron, invented by Frank Rosenblatt, arguably laid the foundations for AI. The electronic analog computer was a learning machine designed to predict whether an image belonged in one of two categories. This revolutionary machine was filled with wires that physically connected different components together. Modern day artificial neural networks that underpin familiar AI like ChatGPT and DALL-E are software versions of the Perceptron, except with substantially more layers, nodes and connections.

Much like modern-day machine learning, if the Perceptron returned the wrong answer, it would alter its connections so that it could make a better prediction of what comes next the next time around. Familiar modern AI systems work in much the same way. Using a prediction-based format, large language models, or LLMs, are able to produce impressive long-form text-based responses and associate images with text to produce new images based on prompts. These systems get better and better as they interact more with users.

In the decade or so after Rosenblatt unveiled the Mark I Perceptron, experts like Marvin Minsky claimed that the world would have a machine with the general intelligence of an average human being by the mid- to late-1970s. But despite some success, humanlike intelligence was nowhere to be found.

It quickly became apparent that the AI systems knew nothing about their subject matter. Without the appropriate background and contextual knowledge, its nearly impossible to accurately resolve ambiguities present in everyday language a task humans perform effortlessly. The first AI winter, or period of disillusionment, hit in 1974 following the perceived failure of the Perceptron.

However, by 1980, AI was back in business, and the first official AI boom was in full swing. There were new expert systems, AIs designed to solve problems in specific areas of knowledge, that could identify objects and diagnose diseases from observable data. There were programs that could make complex inferences from simple stories, the first driverless car was ready to hit the road, and robots that could read and play music were playing for live audiences.

But it wasnt long before the same problems stifled excitement once again. In 1987, the second AI winter hit. Expert systems were failing because they couldnt handle novel information.

The 1990s changed the way experts approached problems in AI. Although the eventual thaw of the second winter didnt lead to an official boom, AI underwent substantial changes. Researchers were tackling the problem of knowledge acquisition with data-driven approaches to machine learning that changed how AI acquired knowledge.

This time also marked a return to the neural-network-style perceptron, but this version was far more complex, dynamic and, most importantly, digital. The return to the neural network, along with the invention of the web browser and an increase in computing power, made it easier to collect images, mine for data and distribute datasets for machine learning tasks.

Fast forward to today and confidence in AI progress has begun once again to echo promises made nearly 60 years ago. The term artificial general intelligence is used to describe the activities of LLMs like those powering AI chatbots like ChatGPT. Artificial general intelligence, or AGI, describes a machine that has intelligence equal to humans, meaning the machine would be self-aware, able to solve problems, learn, plan for the future and possibly be conscious.

Just as Rosenblatt thought his Perceptron was a foundation for a conscious, humanlike machine, so do some contemporary AI theorists about todays artificial neural networks. In 2023, Microsoft published a paper saying that GPT-4s performance is strikingly close to human-level performance.

But before claiming that LLMs are exhibiting human-level intelligence, it might help to reflect on the cyclical nature of AI progress. Many of the same problems that haunted earlier iterations of AI are still present today. The difference is how those problems manifest.

For example, the knowledge problem persists to this day. ChatGPT continually struggles to respond to idioms, metaphors, rhetorical questions and sarcasm unique forms of language that go beyond grammatical connections and instead require inferring the meaning of the words based on context.

Artificial neural networks can, with impressive accuracy, pick out objects in complex scenes. But give an AI a picture of a school bus lying on its side and it will very confidently say its a snowplow 97% of the time.

In fact, it turns out that AI is quite easy to fool in ways that humans would immediately identify. I think its a consideration worth taking seriously in light of how things have gone in the past.

The AI of today looks quite different than AI once did, but the problems of the past remain. As the saying goes: History may not repeat itself, but it often rhymes.

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What you need to know about using artificial intelligence on your smartphone – WTOP

Artificial intelligence is the most talked about technology right now and much of the hype is well-deserved. How accessible is it? Is it a fingertip away?

WTOP's Neal Augenstein reports when and how the public could use artificial intelligence on their phones.

Q: Is it possible to use AI on my smartphone and if so, how do I do it?

A: Artificial intelligence is the most talked about technology right now and much of the hype is well-deserved.

Some are predicting AI will be as transformative as electricity was 100 years ago, in that it will impact virtually every industry in our lives.

If your smartphone is relatively new and updated with the latest operating system, youre using AI-powered tools without even knowing it.

All of the virtual assistants (Siri, Google Assistant, etc.) are using various forms of AI and are developing new capabilities regularly.

Another common area enhanced by AI is your phones camera, both while youre taking pictures and videos, and when youre editing them afterwards.

AI is used to detect the scene being photographed to provide real-time enhancements based on whether its a human face or a landscape, for instance.

Adjusting exposure, contrast and color balance on the fly eliminates the need for the user to make manual adjustments.

AI is also in play for object recognition, such as knowing when the camera is looking at a QR code.

AI-powered editing tools already on your phone may allow you to get rid of items in the background or eliminate wind noise with a few taps of the screen.

If you havent played with the editing tools associated with your phones camera, I recommend exploring there first.

AI algorithms are also used to help optimize battery life and enhance the accuracy of biometric security and voice recognition, as well as the predictive text that seems to be everywhere on our phones.

WTOP's Neal Augenstein speaks with Data Doctors' Ken Colburn on using AI on your mobile phone.

A useful way to start using AI on your phone is by using chatbots as an alternative to search engines.

The best analogy Ive heard is one that compares the process to going to a library. Traditional search engines are like asking the librarian for a specific piece of information and being told which books may contain what you seek and which shelves to start looking through.

Chatbots, on the other hand, will attempt to provide the specific information directly as if the librarian went to the shelf, picked out a book and found the exact page where the information you seek resides.

Chatbots arent a replacement for search engines, but they can be exponentially more efficient when youre travel planning or comparing specifications while car shopping, for instance.

OpenAIs ChatGPT is considered the most advanced chatbot, but it can be a bit overwhelming for beginners. Microsoft is a big investor in OpenAI and has incorporated GPT-4 into their Bing app, which allows you to do side-by-side comparisons of search vs. chatbot results.

Once you download the Bing app for Android or iOS, try using it instead of your normal search engine to see if its more helpful.

Microsofts chatbot, called Copilot, will appear at the bottom center of the app.

New AI apps are being created almost daily, so if youre in search of a specific AI tool, try asking Copilot for suggestions.

Ken Colburn is founder and CEO ofData Doctors Computer Services. Ask any tech question onFacebookorX.

Get breaking news and daily headlines delivered to your email inbox by signing up here.

2024 WTOP. All Rights Reserved. This website is not intended for users located within the European Economic Area.

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TotalEnergies unlocks the potential of generative artificial intelligence for its employees – Total

Download the Press Release (PDF)

Paris, 27 February 2024 A TotalEnergies is among the first organizations to deploy Copilot for Microsoft 365, Microsoft's generative artificial intelligence assistant, for its employees. After making Bing Chat Enterprise, a secure AI chat solution based on internal data, available to employees in August 2023, the Company is pursuing its digital transformation.

In September 2023, TotalEnergies launched a test phase with 300 employees, with positive results. TotalEnergies therefore decided to deploy Copilot for Microsoft 365 for its employees to accelerate its operational transformation. As benefits: an improved operational efficiency and greater user comfort.

TotalEnergies will also provide its teams with Microsoft Power Platform licences, a "low code-no code" application development service enabling them to create, on their own, digital applications that turn their ideas into reality. Employees will thus be able to design solutions connected to other TotalEnergies applications and databases, to solve their simple or complex day-to-day problems more quickly and efficiently.

At the same time, TotalEnergies is implementing a program to support and enhance the skills of its employees in order to help them use these new tools and get the most out of them. In 2024, every employee will receive training dedicated to the use of these new IA tools.

"In line with our pioneering spirit, TotalEnergies is committed to digital transformation and supports its employees so that they can make the most of it. The new technologies of generative artificial intelligence and of 'low code no code' will provide them with the simplification and autonomy they need to put their skills and creativity even further at the service of our company's transition strategy," said Patrick Pouyann, CEO of TotalEnergies.

***

About TotalEnergies

TotalEnergies is a global multi-energy company that produces and markets energies: oil and biofuels, natural gas and green gases, renewables and electricity. Our more than 100,000 employees are committed to energy that is ever more affordable, more sustainable, more reliable and accessible to as many people as possible. Active in nearly 130 countries, TotalEnergies puts sustainable development in all its dimensions at the heart of its projects and operations to contribute to the well-being of people.

TotalEnergies Contacts

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Cautionary Note The terms TotalEnergies, TotalEnergies company or Company in this document are used to designate TotalEnergies SE and the consolidated entities that are directly or indirectly controlled by TotalEnergies SE. Likewise, the words we, us and our may also be used to refer to these entities or to their employees. The entities in which TotalEnergies SE directly or indirectly owns a shareholding are separate legal entities. TotalEnergies SE has no liability for the acts or omissions of these entities. This document may contain forward-looking information and statements that are based on a number of economic data and assumptions made in a given economic, competitive and regulatory environment. They may prove to be inaccurate in the future and are subject to a number of risk factors. Neither TotalEnergies SE nor any of its subsidiaries assumes any obligation to update publicly any forward-looking information or statement, objectives or trends contained in this document whether as a result of new information, future events or otherwise. Information concerning risk factors, that may affect TotalEnergies financial results or activities is provided in the most recent Registration Document, the French-language version of which is filed by TotalEnergies SE with the French securities regulator Autorit des Marchs Financiers (AMF), and in the Form 20-F filed with the United States Securities and Exchange Commission (SEC).

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