Category Archives: Artificial Intelligence

Artificial intelligence (AI) has been recognized as the most disruptive technology since Q3 2021, and this holds true across various industries, including the retail sector.

Retailers are increasingly investing in AI with the goal of boosting sales, stabilizing supply chains, improving planning processes, and enhancing customer relations.

One area where AI is making a significant impact is in supply chain forecasting. Through machine learning, retailers can accurately predict demand by considering hundreds of influencing factors. This enables better planning across merchandising, supply chains, and operations, providing visibility into future demand for every product in every store and channel.

Retailers such as One Stop have already implemented AI forecasting solutions and have reported positive results. After just four months of using an AI forecasting solution, One Stop saw a 5% increase in store availability across their entire range, leading to a significant increase in sales.

AI is also helping retailers cut operational costs through the use of chatbots. Automated cashier-free stores, like Amazon Go, have been successful in reducing queues and operational expenses. AI-powered chatbots are being adopted by brands like Burberry to enhance customer service, improve searchability, and provide personalized product suggestions.

Pricing and clearance optimization software is another area where AI is transforming the retail sector. These solutions automate markdowns and clearance processes, eliminating manual tasks and reducing the risk of excess stock. Retailers can identify products for clearance and set optimized discounts based on desired outcomes. This helps improve margins and inventory turnover.

The use of AI in the retail sector is diverse and constantly evolving. Companies that embrace AI technology will position themselves as industry leaders, while those who overlook its potential may struggle to keep up with the competition. The adoption of AI will play a crucial role in determining the winners and losers in the retail sector of tomorrow.

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The Impact of Artificial Intelligence in the Retail Sector - Fagen wasanni

Overcoming IT Hurdles: A Comprehensive Guide to Solving IT Challenges with Artificial Intelligence

The world of information technology (IT) is constantly evolving, bringing forth new challenges that need innovative solutions. One such solution that has gained significant traction in recent years is Artificial Intelligence (AI). By leveraging AI, businesses can overcome a myriad of IT hurdles, from data management to cybersecurity threats, and improve their overall operational efficiency.

The first major challenge that AI can help address is data management. In the digital age, businesses generate and collect vast amounts of data. Managing this data, ensuring its accuracy, and extracting meaningful insights from it can be a daunting task. However, AI, with its machine learning capabilities, can automate data management processes, analyze complex data sets, and provide actionable insights. This not only saves time and resources but also helps businesses make data-driven decisions.

Next, AI can significantly enhance cybersecurity measures. With cyber threats becoming increasingly sophisticated, traditional security measures are often insufficient. AI can help by constantly learning from these threats and adapting security measures accordingly. For instance, AI can identify patterns in cyber-attacks, predict potential threats, and implement preventive measures, thereby providing a robust defense against cyber threats.

Moreover, AI can streamline IT operations by automating routine tasks. IT departments often spend a significant amount of time on mundane tasks such as system maintenance and troubleshooting. AI can automate these tasks, freeing up IT professionals to focus on more strategic initiatives. Additionally, AI can predict IT system failures and take corrective action before the issue escalates, thereby minimizing downtime and improving system reliability.

Another area where AI can make a significant impact is customer service. With AI-powered chatbots, businesses can provide 24/7 customer support, resolve queries promptly, and improve customer satisfaction. These chatbots can learn from past interactions, thereby enhancing their ability to resolve customer queries over time.

Furthermore, AI can help in resource allocation. By analyzing past data, AI can predict future resource requirements and help businesses plan accordingly. This can result in cost savings and improved efficiency. For instance, AI can predict when a business might experience a surge in website traffic and allocate resources accordingly to prevent website downtime.

Finally, AI can aid in decision-making. By analyzing data and providing insights, AI can help businesses make informed decisions. Whether its deciding on the best marketing strategy or identifying potential areas of investment, AI can provide valuable input that can drive business growth.

In conclusion, AI presents a comprehensive solution to various IT challenges. By automating routine tasks, enhancing cybersecurity, improving customer service, aiding in resource allocation, and facilitating decision-making, AI can significantly improve business operations. However, its important to note that the successful implementation of AI requires a strategic approach. Businesses need to clearly define their objectives, invest in the right AI tools, and train their staff to effectively use these tools. With the right approach, businesses can harness the power of AI to overcome IT hurdles and drive growth.

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Solving IT Challenges with Artificial Intelligence: A Comprehensive ... - Fagen wasanni

Twenty years ago, the advent of the internet led many to worry about their job security. Yet the rapid digitisation that ensued created millions of careers that didnt exist before. By 2018, digital jobs accounted for 7.7% of the UK economy.

History does tend to repeat itself, and right now, there are scores of headlines popping up every day about the latest threat borne of Silicon Valley; artificial intelligence (AI) and machine learning (ML). Thanks, in part, to a new wave of freely available AI-powered chatbots, businesses and consumers alike are becoming aware of the technologys extensive capabilities.

While this has opened up fierce discussion about regulation even among the brightest minds in tech, there is also optimism about how AI could revolutionise the enterprise. Rather than fearing it may replace everyones jobs there are many examples of why this wont happen in both technical and creative roles it is easy to see how it could make work more enjoyable by automating dull, repetitive tasks.

This is particularly true in growing businesses, where higher-level employees may be bogged down by mundane tasks instead of focusing on strategy and other complex responsibilities.

For instance, no one wants to dig around their desk or car footwells for crumpled-up receipts when submitting expenses. Similarly, most CFOs dont want to be stomping about workstations, chasing staff for paperwork. Dedicated expense management apps enable employees to take a photo of their receipt as soon as they get it, automatically drawing out the relevant data to start a pain-free submission process.

An example of this can be found with Barnsley Metropolitan Borough Council, which recently automated its expense management processes with Concur Expense, a solution from SAP Concur. The council wanted to eliminate manual processes and create digital workflows [to] provide the highest possible levels of service to residents. After installing Concur Expense, mobile teams (like social workers) could input expenses on the go through an app. The time saved in expense entry and the reduced number of human errors thanks to AI-powered automation decreased the average reimbursement time from six weeks to three days.

Implementing a T&E management software powered by AI has also helped Barnsley Metropolitan Borough Council focus on its sustainability. The data allows it to better monitor its grey fleet the personal vehicles being used for business purposes and therefore its carbon footprint too. The council can now make more informed decisions about its travel policy, and appropriately encourage employees to make use of public transport.

David Robinson, Service Director at the council, said: We want to adopt modern ways of working to give people the right work-life balance and attract the best talent. Concur Expense is a great example of how we can increase support for digital initiatives among employees by making sure theyre not out of pocket while we process claims.

Integrating AI into workplace software is nothing new, of course. But travel and expense management has been under-explored, despite being a data-rich area and, therefore, perfect for machine learning. There is also demand; research from Forrester Consulting has shown that 59% of decision-makers say that employee frustration with their expense process had a large or very large negative impact on the entire company.

Advanced algorithms can analyse and categorise expense data by recognising patterns and using natural language processing techniques. They auto-approve low-risk claims, eliminating the need for manual entry and reducing errors. As these algorithms process more expenses, they get better at knowing what is safe to approve without human intervention.

Automation reduces the chances of anything slipping through the cracks. Research has shown that 62% of finance leaders find that digital tools help them manage expenses more effectively across their organisations. Studies have also shown that over half of companies implementing an integrated travel and expense solution increase their scalability and flexibility.

Moreover, AI can defend the company against fraud by comparing the expense data against predefined rules and benchmarks and flagging any potential violations. It also helps organisations follow all compliance and regulatory requirements, something thats often only an afterthought. From a business intelligence perspective, too, technology can highlight cost-saving opportunities, generating reports for decision-makers from collated travel and expense data.

The minds at SAP Concur know that implementing AI and ML into finance processes can be intimidating. However, its software is well tried and tested, having been adopted by over 48,000 businesses since the early 1990s.

Expense management has been undergoing optimisation with AI and ML since long before other areas of corporate finance. Indeed, automating small, repetitive tasks like using Concur Expense to submit and approve receipts is a good starting point.

In the future, we can expect AI to completely transform expense management, resulting in increased company efficiency, savings from better financial management and minimised environmental impact. Its widespread implementation is expected to result in a 7% increase in GDP over the next ten years.

If you want to learn more about automating your expenses with SAP Concur, visit this website.

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The role of artificial intelligence in the world of the CFO starts with ... - TechHQ

As more businesses adopt artificial intelligence (AI) tools, venture capitalists (VCs) are putting more money into the industry.

Nearly three-quarters of global VCs invested in AI over the past year, with investors identifying AI as the technology with the most disruption potential, according to a recent survey by PitchBook and Collision.

Seventy-four percent of those surveyed said they made at least one investment in AI or machine learning (ML) startups in the last 18 months, and 14% claimed they had made more than six investments in the space.

The number of companies that use AI has also more than doubled since 2017, according to research by McKinsey. Service operations optimization, the creation of new AI-based tools, and customer service analytics are the most widely used cases of AI.

However, funding activities have taken a major blow due to uncertain macroeconomic conditions and rising rates. VCs formed $13 billion in funds during the first quarter of 2023, compared to $78.1 billion in the same period a year ago, according to EY. More than half of investors PitchBook surveyed said they arent looking to raise funds, while 54% suggested they believe that raising funds will be difficult in the next 12 months.

Despite being battered by economic headwinds and rising rates, nearly 68% of respondents claim that their pace of investment over the last 18 months remains near normal. Only 3.4% of respondents said that they have halted investments for the time being.

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Majority of Venture Capitalists Invested in Artificial Intelligence ... - Investopedia

Imagine I told you in 1970 that I was going to invent a wondrous tool. This new tool would make it possible for anyone with access and most of humanity would have access to quickly communicate and collaborate with anyone else. It would store nearly the sum of human knowledge and thought up to that point, and all of it would be searchable, sortable and portable. Text could be instantly translated from one language to another, news would be immediately available from all over the world, and it would take no longer for a scientist to download a journal paper from 15 years ago than to flip to an entry in the latest issue.

What would you have predicted this leap in information and communication and collaboration would do for humanity? How much faster would our economies grow?

Now imagine I told you that I was going to invent a sinister tool. (Perhaps, while telling you this, I would cackle.) As people used it, their attention spans would degrade, as the tool would constantly shift their focus, weakening their powers of concentration and contemplation. This tool would show people whatever it is they found most difficult to look away from which would often be what was most threatening about the world, from the worst ideas of their political opponents to the deep injustices of their society. It would fit in their pockets and glow on their night stands and never truly be quiet; there would never be a moment when people could be free of the sense that the pile of messages and warnings and tasks needed to be checked.

What would you have thought this engine of distraction, division and cognitive fracture would do to humanity?

Thinking of the internet in these terms helps solve an economic mystery. The embarrassing truth is that productivity growth how much more we can make with the same number of people and factories and land was far faster for much of the 20th century than it is now. We average about half the productivity growth rate today that we saw in the 1950s and 60s. That means stagnating incomes, sluggish economies and a political culture thats more about fighting over what we have than distributing the riches and wonders weve gained. So what went wrong?

You can think of two ways the internet could have sped up productivity growth. The first way was obvious: by allowing us to do what we were already doing and do it more easily and quickly. And that happened. You can see a bump in productivity growth from roughly 1995 to 2005 as companies digitized their operations. But its the second way that was always more important: By connecting humanity to itself and to nearly its entire storehouse of information, the internet could have made us smarter and more capable as a collective.

I dont think that promise proved false, exactly. Even in working on this article, it was true for me: The speed with which I could find information, sort through research, contact experts its marvelous. Even so, I doubt I wrote this faster than I would have in 1970. Much of my mind was preoccupied by the constant effort needed just to hold a train of thought in a digital environment designed to distract, agitate and entertain me. And I am not alone.

Gloria Mark, a professor of information science at the University of California, Irvine, and the author of Attention Span, started researching the way people used computers in 2004. The average time people spent on a single screen was 2.5 minutes. I was astounded, she told me. That was so much worse than Id thought it would be. But that was just the beginning. By 2012, Mark and her colleagues found the average time on a single task was 75 seconds. Now its down to about 47.

This is an acid bath for human cognition. Multitasking is mostly a myth. We can focus on one thing at a time. Its like we have an internal whiteboard in our minds, Mark said. If Im working on one task, I have all the info I need on that mental whiteboard. Then I switch to email. I have to mentally erase that whiteboard and write all the information I need to do email. And just like on a real whiteboard, there can be a residue in our minds. We may still be thinking of something from three tasks ago.

The cost is in more than just performance. Mark and others in her field have hooked people to blood pressure machines and heart rate monitors and measured chemicals in the blood. The constant switching makes us stressed and irritable. I didnt exactly need experiments to prove that I live that, and you probably do, too but it was depressing to hear it confirmed.

Which brings me to artificial intelligence. Here Im talking about the systems we are seeing now: large language models like OpenAIs GPT-4 and Googles Bard. What these systems do, for the most part, is summarize information they have been shown and create content that resembles it. I recognize that sentence can sound a bit dismissive, but it shouldnt: Thats a huge amount of what human beings do, too.

Already, we are being told that A.I. is making coders and customer service representatives and writers more productive. At least one chief executive plans to add ChatGPT use in employee performance evaluations. But Im skeptical of this early hype. It is measuring A.I.s potential benefits without considering its likely costs the same mistake we made with the internet.

I worry were headed in the wrong direction in at least three ways.

One is that these systems will do more to distract and entertain than to focus. Right now, the large language models tend to hallucinate information: Ask them to answer a complex question, and you will receive a convincing, erudite response in which key facts and citations are often made up. I suspect this will slow their widespread use in important industries much more than is being admitted, akin to the way driverless cars have been tough to roll out because they need to be perfectly reliable rather than just pretty good.

A question to ask about large language models, then, is where does trustworthiness not matter? Those are the areas where adoption will be fastest. An example from media is telling, I think. CNET, the technology website, quietly started using these models to write articles, with humans editing the pieces. But the process failed. Forty-one of the 77 A.I.-generated articles proved to have errors the editors missed, and CNET, embarrassed, paused the program. BuzzFeed, which recently shuttered its news division, is racing ahead with using A.I. to generate quizzes and travel guides. Many of the results have been shoddy, but it doesnt really matter. A BuzzFeed quiz doesnt have to be reliable.

A.I. will be great for creating content where reliability isnt a concern. The personalized video games and childrens shows and music mash-ups and bespoke images will be dazzling. And new domains of delight and distraction are coming: I believe were much closer to A.I. friends, lovers and companions becoming a widespread part of our social lives than society is prepared for. But where reliability matters say, a large language model devoted to answering medical questions or summarizing doctor-patient interactions deployment will be more troubled, as oversight costs will be immense. The problem is that those are the areas that matter most for economic growth.

Marcela Martin, BuzzFeeds president, encapsulated my next worry nicely when she told investors, Instead of generating 10 ideas in a minute, A.I. can generate hundreds of ideas in a second. She meant that as a good thing, but is it? Imagine that multiplied across the economy. Someone somewhere will have to process all that information. What will this do to productivity?

One lesson of the digital age is that more is not always better. More emails and more reports and more Slacks and more tweets and more videos and more news articles and more slide decks and more Zoom calls have not led, it seems, to more great ideas. We can produce more information, Mark said. But that means theres more information for us to process. Our processing capability is the bottleneck.

Email and chat systems like Slack offer useful analogies here. Both are widely used across the economy. Both were initially sold as productivity boosters, allowing more communication to take place faster. And as anyone who uses them knows, the productivity gains though real are more than matched by the cost of being buried under vastly more communication, much of it junk and nonsense.

The magic of a large language model is that it can produce a document of almost any length in almost any style, with a minimum of user effort. Few have thought through the costs that will impose on those who are supposed to respond to all this new text. One of my favorite examples of this comes from The Economist, which imagined NIMBYs but really, pick your interest group using GPT-4 to rapidly produce a 1,000-page complaint opposing a new development. Someone, of course, will then have to respond to that complaint. Will that really speed up our ability to build housing?

You might counter that A.I. will solve this problem by quickly summarizing complaints for overwhelmed policymakers, much as the increase in spam is (sometimes, somewhat) countered by more advanced spam filters. Jonathan Frankle, the chief scientist at MosaicML and a computer scientist at Harvard, described this to me as the boring apocalypse scenario for A.I., in which we use ChatGPT to generate long emails and documents, and then the person who received it uses ChatGPT to summarize it back down to a few bullet points, and there is tons of information changing hands, but all of it is just fluff. Were just inflating and compressing content generated by A.I.

When we spoke, Frankle noted the magic of feeding a 100-page Supreme Court document into a large language model and getting a summary of the key points. But was that, he worried, a good summary? Many of us have had the experience of asking ChatGPT to draft a piece of writing and seeing a fully formed composition appear, as if by magic, in seconds.

My third concern is related to that use of A.I.: Even if those summaries and drafts are pretty good, something is lost in the outsourcing. Part of my job is reading 100-page Supreme Court documents and composing crummy first drafts of columns. It would certainly be faster for me to have A.I. do that work. But the increased efficiency would come at the cost of new ideas and deeper insights.

Our societywide obsession with speed and efficiency has given us a flawed model of human cognition that Ive come to think of as the Matrix theory of knowledge. Many of us wish we could use the little jack from The Matrix to download the knowledge of a book (or, to use the movies example, a kung fu master) into our heads, and then wed have it, instantly. But that misses much of whats really happening when we spend nine hours reading a biography. Its the time inside that book spent drawing connections to what we know and having thoughts we would not otherwise have had that matters.

Nobody likes to write reports or do emails, but we want to stay in touch with information, Mark said. We learn when we deeply process information. If were removed from that and were delegating everything to GPT having it summarize and write reports for us were not connecting to that information.

We understand this intuitively when its applied to students. No one thinks that reading the SparkNotes summary of a great piece of literature is akin to actually reading the book. And no one thinks that if students have ChatGPT write their essays, they have cleverly boosted their productivity rather than lost the opportunity to learn. The analogy to office work is not perfect there are many dull tasks worth automating so people can spend their time on more creative pursuits but the dangers of overautomating cognitive and creative processes are real.

These are old concerns, of course. Socrates questioned the use of writing (recorded, ironically, by Plato), worrying that if men learn this, it will implant forgetfulness in their souls; they will cease to exercise memory because they rely on that which is written, calling things to remembrance no longer from within themselves but by means of external marks. I think the trade-off here was worth it I am, after all, a writer but it was a trade-off. Human beings really did lose faculties of memory we once had.

To make good on its promise, artificial intelligence needs to deepen human intelligence. And that means human beings need to build A.I. and build the workflows and office environments around it, in ways that dont overwhelm and distract and diminish us. We failed that test with the internet. Lets not fail it with A.I.

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Opinion | Beyond the Matrix Theory of the Human Mind - The New York Times

New Products, Features and Cross-Platform Integrations Accelerate Identity and Cloud Security

CyberArk (NASDAQ:CYBR), theIdentity Securitycompany, today announced new products and features across the CyberArk Identity Security Platform, making it the most powerful platform of its kind. Investments to enhance cloud security and deliver automation and artificial intelligence (AI) innovations across the platform make it easier than ever to apply intelligent privilege controls to all identities human and non-human from a single vendor.

The rapid acceleration of identities is part of what makes a unified approach to advancing Identity Security so important. Treating identities differently with stand-alone technologies misses the mark and exposes risk, said Peretz Regev, chief product officer, CyberArk. Our unified Identity Security platform breaks down those silos by contextually authenticating identities, then dynamically authorizing the least amount of privilege required. Additionally, we continue to strategically expand our use of machine learning and artificial intelligence to improve customers defensive capabilities to counter attacker innovation.

With CyberArks single, unified Identity Security platform organizations can achieve Zero Trust and least privilege with complete visibility and enable secure access for any identity from anywhere and to the widest range of resources or environments. TheCyberArk Identity Security Platformhelps customers apply intelligent privilege controls to reduce risk for all identities and consolidate vendors while delivering operational efficiencies and achieving a faster ROI.

CyberArk leads the market with innovative new features and investments in automation and artificial intelligence to improve Identity Security and enable organizations to implement proactive controls and defensive strategies. Key innovations in these areas include:

Enhancements across the CyberArk Identity Security Platform focus on further improving security, adoption and user experience. Additional new capabilities driving value across the platform will include:

In addition, at IMPACT 23 CyberArk also announcedCyberArk Secure Browser, a first-of-its-kind Identity Security-based browser.

About CyberArk CyberArk(NASDAQ:CYBR) is the global leader in Identity Security. Centered onintelligent privilege controls, CyberArk provides the most comprehensive security offering for any identity human or machine across business applications, distributed workforces, hybrid cloud environments and throughout the DevOps lifecycle. The worlds leading organizations trust CyberArk to help secure their most critical assets. To learn more about CyberArk, visithttps://www.cyberark.com, read theCyberArk blogsor follow onLinkedIn,Twitter,FacebookorYouTube.

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CyberArk Supercharges Identity Security Platform with Automation ... - CXOToday.com

Adobe (ADBE 5.95%) is bringing artificial intelligence to Photoshop, and it makes all the sense in the world. As Travis Hoium covers in this video, if AI ends up being an incremental technology improvement it will make Adobe's business stronger.

*Stock prices used were end-of-day prices of May 24, 2023. The video was published on May 24, 2023.

Travis Hoium has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Adobe. The Motley Fool recommends the following options: long January 2024 $420 calls on Adobe and short January 2024 $430 calls on Adobe. The Motley Fool has a disclosure policy.Travis Hoium is an affiliate of The Motley Fool and may be compensated for promoting its services. If you choose to subscribe throughtheir link they will earn some extra money that supports their channel. Their opinions remain their own and are unaffected by The Motley Fool.

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Photoshop Is Getting Artificial Intelligence -- Why That's a Big Deal ... - The Motley Fool

One way to break the cycle of drudgery, at least from her point of view, is by effective use of messaging software, particularly when enhanced by artificial intelligence.

As the newly christened chief executive of Slack, the messaging app, you would expect Jones to say that. She is all-in on making office workers days more productive. Toward that end, on May 4, Jones announced a suite of Slack programs that use artificial intelligence under the brand name Slack GPT. These are designed to make colleagues communications more efficient, including by providing conversation summaries and writing assistance, and to make it easier for salespeople to respond to clients and prospects, by providing alerts of sales leads and instant research. These AI programs will also help Jones and her colleagues integrate the consumer-facing Slack app with the business-focused tools offered by Slacks parent company, Salesforce.

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Jones was already one of the most prominent Latinas in the high-tech sector when she became CEO about four months ago, taking over for Slack cofounder Stewart Butterfield. Now, as the head of one of the best-known software programs used in modern office life, shes also one of the most prominent tech executives in Greater Boston.

Although Salesforce is based in San Francisco, Jones lives in Cambridge. She moved to Greater Boston more than 15 years ago from the Seattle area as a Microsoft executive, in large part because her husband wanted to return to his home state. She continued to rise up the ranks at Microsoft, before leaving in 2015 to be VP of software product management for speaker maker Sonos in Boston. Salesforce called four years later; she liked how its e-commerce options allow companies like Sonos to stay independent, and took a job helping oversee that part of Salesforces business.

Jones said she was surprised when Butterfield reached out about taking over Slack. But she calls the past four months the best, you know, four months Ive had in my career even though it involves plenty of travel. She has bounced around from Australia to London to Toronto, with plenty of visits to San Francisco.

Chamber chief executive Jim Rooney thought Jones would be a perfect keynote speaker for this years annual meeting and invited her through chamber members Thea James and Betty Francisco, who volunteer alongside Jones at Boston nonprofit Compass Working Capital.

About that AI that Jones talked about at the chamber: She has been impressed by how quickly big companies are adopting Slack GPT. Every customer is knocking on my door, Jones said. Theyre like, Hey, just protect my data, but I need this.

As the states economic development secretary, Yvonne Hao is leading the charge to update the official economic development plan for Massachusetts something required by state law to happen every four years. She certainly wont be at a loss for feedback.

Last week, Hao told members of real estate trade group NAIOP Massachusetts that more than 200 people attended the first two regional listening sessions, in Springfield and Worcester from big companies and small businesses, nonprofits and city councils. She plans to finish the report by the end of the year and is relying in part on an advisory council, which includes NAIOP chief executive Tamara Small as a member.

One possible reason Hao is getting so much feedback: rising concerns about the states economic competitiveness.

At the NAIOP event, Jake Grossman of the Grossman Companies said he worries about taxes and housing affordability. Can you give me a little therapy session? Grossman asked Hao. Whats the good stuff thats happening?

Hao said shes hustling to make the case at every turn for why companies should stay and grow here, arguments that tend to focus on our well-educated talent pool. She said she heard that a chief executive was being recruited to relocate to North Carolina, so she hopped on the phone with him to explain why he should stay. And she noted that Governor Maura Healey has hired Quentin Palfrey and Will Rasky to go after all the federal funds they can find for Massachusetts. Other states have this muscle developed [but] we havent, she said of lobbying Washington.

She knows Massachusetts has been one of the few states to lose people during the pandemic but is determined to reverse that trend.

This is not the time to hang out and rest, Hao said. We have real issues we have to fix. If you wait too long ... by the time you realize youve lost, its too late.

As the founder of Resilient Coders training program for people of color, David Delmar Sentes has helped a generation of Black and Latino tech workers enter the workforce.

Now that the tech sector is experiencing a downturn, Delmar Sentes worries many of those alums are being left behind, and that the corporate diversity commitments made in recent years are slipping away. (Delmar Sentes left Resilient Coders last year to finish his book on this topic, What We Build with Power.) Black workers, he said, have been disproportionately affected by all the tech layoffs, and diversity and equity budgets have been slashed.

Thats why he and Pariss Chandler, founder of the Black Tech Pipeline, among others, are launching a campaign for worker-led equity in the field. Theyll hold their first organizing meeting on June 12. Among the reforms Delmar Sentes wants: companies getting serious about dropping bachelors degrees from the list of job requirements. He also hopes for the creation of some sort of organization think of it as a Better Business Bureau, but for DEI that can track companies that are doing well, and the ones that are performing poorly.

Resilient Coders and other organizations like it are functionally marching into the wind, he said. If you do that long enough, you wonder what it would be like to change the direction of the wind.

Terry Richardson has led major sales efforts for two giant tech companies, Hewlett Packard Enterprise and AMD the kind of jobs that can put you on the road more often than youre home.

While at AMD, Richardson was deciding whether to finally retire, or to find a job a little closer to home. He ended up picking the latter option, when Josh Dinneen rang him up. Dinneen was moving up to president at Portsmouth, N.H-based IT services and cybersecurity provider GreenPages, which also has an office in Charlestown. And Dinneen wanted someone he could trust to take over his previous role there as chief revenue officer. Thus, the invite was extended to Richardson. He joined GreenPages, which is owned by Boston private equity firm Abry Partners, on May 1.

Richardson said he liked the technology expertise and the people at the 310-person firm. Plus, its hard to argue with the lifestyle improvements, because most clients are in and around New England as opposed to the marathon trips Richardson took on almost a weekly basis. While the GreenPages headquarters in Portsmouth isnt exactly a short drive away from his home in Hopkinton, at least he knows he can finish the day in his own bed. Its time, finally, to stop the running.

Jon Chesto can be reached at jon.chesto@globe.com. Follow him on Twitter @jonchesto.

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Slack CEO looks to artificial intelligence for help in rolling out new ... - The Boston Globe

Teleo co-founder and CEO Vinay Shet discusses the potential impact of artificial intelligence on manufacturing and construction jobs on "The Claman Countdown."

FIRST ON FOX Artificial intelligence has entered the construction industry, and early adopters say the efficiencies and cost-cutting measures will revolutionize the $10 trillion sector of the global economy for the better.

Supply chain and building material software company DigiBuild has been using OpenAI's ChatGPT to bolster its program for months, and is set to unveil the results at an event in Miami on Wednesday evening.

DigiBuild, a supply chain and building material software company, has been using ChatGPT for months.

But ahead of the announcement, DigiBuild CEO Robert Salvador gave FOX Business an exclusive sneak peek of how the powerful AI tool has improved efficiency and slashed costs for the firm's clients, and he says the technology will be "market changing."

The construction industry is still dogged by the high material costs and supply chain woes brought on by the pandemic, and DigiBuild's software aims to help developers and contractors save money and improve their schedules. The help of AI has provided a remarkable boost to that end.

UNPLEASANT CUSTOMER SERVICE CALLS, ENDLESS WAIT TIMES MAY HAVE TECH FIX

To the company's knowledge, DigiBuild is the first to introduce ChatGPTinto the construction supply chain, and the firm has some inside help. The building software firm is backed by major investors, including Y Combinator which trained OpenAI CEO Sam Altman and has an exclusive Slack channel with OpenAI that allows experts to build together.

Construction workers are shown with the Manhattan skyline and Empire State Building behind them in Brooklyn, New York City, on Jan. 24, 2023. (Ed Jones / AFP via Getty Images / Getty Images)

DigiBuild has been around five years and has automated the job of sifting through suppliers to find materials and working out scheduling. Now, what used to take a team of humans hundreds of labor hours using Excel spreadsheets, notebooks and manual phone calls has been reduced to a matter of seconds with the help of language learning models.

"ChatGPT has taken us to the next level," Salvador said. "Supersonic."

AI DATA LEAK CRISIS: NEW TOOL PREVENTS COMPANY SECRETS FROM BEING FED TO CHATGPT

"Instead of spending multiple hours probably getting a hold of maybe five or six suppliers, ChatGPT can find 100 of them and even automate outreach and begin communications with those 100 suppliers and say, 'Hey, we're DigiBuild. We need to find this type of door, can you provide a quote and send it back here?'" he said. "We can talk to 100 suppliers in one minute versus maybe a handful in a couple hours."

DigiBuild CEO Robert Salvador says ChatGPT has taken the company "supersonic."

The CEO offered a real-world example of a job where material costs were literally slashed by more than half using the new technology.

One of DigiBuild's clients, VCC Construction, needed closet shelving for a project in Virginia, and the builder could only find one quote for $150,000 with limited availability. With the click of a button, DigiBuild was able to find a vendor in the Midwest that provided the shelving and delivered it within weeks for $70,000.

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Salvador says to imagine those results for a $500 million job or across the industry. He expects AI technology to become widely adopted.

"Before companies like us, the construction industry was still early in its digital transformation they were late to the party," he told FOX Business. But now, "It's very much going all in on that, finally."

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AI set to transform construction industry - Fox Business

Contributing columnist|AddFollow

April 26, 2023 at 6:30 a.m. EDT

Tech and democracy are not friends right now. We need to change that fast.

As Ive discussed previously in this series, social media has already knocked a pillar out from under our democratic institutions by making it exceptionally easy for people with extreme views to connect and coordinate. The designers of the Constitution thought geographic dispersal would put a brake on the potential power of dangerous factions. But people no longer need to go through political representatives to get their views into the public sphere.

Our democracy is reeling from this impact. We are only just beginning the work of renovating our representative institutions to find mechanisms (ranked choice voting, for instance) that can replace geographic dispersal as a brake on faction.

Now, here comes generative artificial intelligence, a tool that will help bad actors further accelerate the spread of misinformation.

A healthy democracy could govern this new technology and put it to good use in countless ways. It would also develop defenses against those who put it to adversarial use. And it would look ahead to probable economic transformation and begin to lay out plans to navigate what will be a rapid and startling set of transitions. But is our democracy ready to address these governance challenges?

Im worried about the answer to that, which is why I joined a long list of technologists, academics and even controversial visionaries such as Elon Musk in signing an open letter calling for a pause for at least six months of "the training of AI systems more powerful than GPT-4. This letter was occasioned by the release last month of GPT-4 from the lab OpenAI. GPT-4 significantly improves on the power and functionality of ChatGPT, which was released in November.

The field of technology is convulsed by a debate about whether we have reached the Age of AGI. Not just an Age of AI, where machines and software, like Siri, perform specific and narrow tasks, but an Age of Artificial General Intelligence, in which technology can meet and match humans on just about any task. This would be a game changer giving us not just more problems of misinformation and fraud, but also all kinds of unpredictable emergent properties and powers from the technology.

The newest generative foundation models powering GPT-4 can match the best humans in a range of fields, from coding to the LSAT. But is the power of generative AI evidence of the arrival of what has for some been a long-sought goal artificial general intelligence? Bill Gates, cofounder of Microsoft, which has sought to break away from its rivals via intense investment in OpenAI, says no and argues that the capability of GPT-4 and other large language models is still constrained to limited tasks. But a team of researchers at Microsoft Research, in a comprehensive review of the capability of GPT-4, says yes. They see sparks of artificial general intelligence in the newest machine-learning models. My own take is that the research team is right. (Disclosure: My research lab has received funding support from Microsoft Research.)

But regardless of which side of the debate one comes down on, and whether the time has indeed come (as I think it has) to figure out how to regulate an intelligence that functions in ways we cannot predict, it is also the case that the near-term benefits and potential harms of this breakthrough are already clear, and attention must be paid. Numerous human activities including many white-collar jobs can now be automated. We used to worry about the impacts of AI on truck drivers; now its also the effects on lawyers, coders and anyone who depends on intellectual property for their livelihood. This advance will increase productivity but also supercharge dislocation.

In comments that sound uncannily as if from the early years of globalization, Gates said this about the anticipated pluses and minuses: When productivity goes up, society benefits because people are freed up to do other things, at work and at home. Of course, there are serious questions about what kind of support and retraining people will need. Governments need to help workers transition into other roles.

And we all know how that went.

For a sense of the myriad things to worry about, consider this (partial) list of activities that OpenAI knows its technology can enable and that it therefore prohibits in its usage policies:

Illegal activity. Child sexual-abuse material. Generation of hateful, harassing or violent content. Generation of malware. Activity that has high risk of physical harm, including: weapons development; military and warfare; management or operation of critical infrastructure in energy, transportation and water; content that promotes, encourages or depicts acts of self-harm. Activity that has a high risk of economic harm, including: multilevel marketing, gambling, payday lending, automated determinations of eligibility for credit, employment, educational institutions or public assistance services. Fraudulent or deceptive activity, including: scams, coordinated inauthentic behavior, plagiarism, astroturfing, disinformation, pseudo-pharmaceuticals. Adult content. Political campaigning or lobbying by generating high volumes of campaign materials. Activities that violate privacy. Unauthorized practice of law or medicine or provision of financial advice.

The point of the open letter is not to say that this technology is all negative. On the contrary. There are countless benefits to be had. It could at long last truly enable the personalization of learning. And if we can use what generative AI is poised to create to compensate internet users for the production of the raw data its built upon treat that human contribution as paid labor, in other words we might be able to redirect the basic dynamics of the economy away from the ever-greater concentration of power in big tech.

But whats the hurry? We are simply ill-prepared for the impact of yet another massive social transformation. We should avoid rushing into all of this with only a few engineers at a small number of labs setting the direction for all of humanity. We need a breather for some collective learning about what humanity has created, how to govern it, and how to ensure that there will be accountability for the creation and use of new tools.

There are already many things we can and should do. We should be making scaled-up public-sector investments into third-party auditing, so we can actually know what models are capable of and what data theyre ingesting. We need to accelerate a standards-setting process that builds on work by the National Institute of Standards and Technology. We must investigate and pursue compute governance, which means regulation of the use of the massive amounts of energy necessary for the computing power that drives the new models. This would be akin to regulating access to uranium for the production of nuclear technologies.

More than that, we need to strengthen the tools of democracy itself. A pause in further training of generative AI could give our democracy the chance both to govern technology and to experiment with using some of these new tools to improve governance. The Commerce Department recently solicited input on potential regulation for the new AI models; what if we used some of the tools the AI field is generating to make that public comment process even more robust and meaningful?

We need to govern these emerging technologies and also deploy them for next-generation governance. But thinking through the challenges of how to make sure these technologies are good for democracy requires time we havent yet had. And this is thinking even GPT-4 cant do for us.

Danielle Allen on renovating democracy

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Opinion | Artificial generative intelligence could prove too much for democracy - The Washington Post