When recent school funding initiatives made it possible for the municipality to invest in education upgrades, Chuck Marzec, the district’s director of technology, turned to Larry Meister, president of IT solutions provider Mercury Networks. Meister, who has worked with the district for over a decade, collaborated with Marzec to determine which products and solutions would maximize learning benefits for the most students. Considering the timing, pricing, and available funding, they concluded that the LG CreateBoards could transform the experiences of every student and deliver forward-thinking classrooms that prepare students for a tech-filled world and job market.

The district last updated its projection-based classroom systems in 2012, before the explosion of new touch-sensitive smart boards that are sweeping across the education landscape. Attractive pricing helped convince the district that smart boards would be the most impactful, sustainable and widely deployable solution, offering greater capabilities than existing systems while standardizing every classroom to simplify daily management and long-term maintenance.

“LG’s easy-to-use CreateBoard interactive digital boards come at an incredible value, making them the best fit for Jamestown Public Schools. The district initially considered outfitting about half of its classrooms with a competitor product at double the price. With the CreateBoard, they’re essentially doubling their investment, creating streamlined experiences for staff and students in every room and school,” Meister explained. “The district’s previous projection systems were single-room solutions lacking significant communication options and new advances in interactivity or cloud-based learning tools. Now, with the LG CreateBoards, they have a unified 500+ display network that can be monitored, managed, and used to distribute content from a single location for morning announcements or emergencies. Additionally, the ability to set automatic on/off schedules ensures no energy is wasted, eliminating one task for today’s busy teachers.”

The district is excited about what the technology can unleash in terms of classroom participation and faculty lesson plans, including simple access to popular web-based tools such as Google Classroom. The 40-point multi-touch digital displays allow a variety of interactive lesson plans and activities that can invite multiple students to use the board at once, in addition to convenient streaming and mobile device connections for educators and students alike. For instance, teachers can quickly log in to their accounts for Google and other services by scanning an on-screen QR code with their smartphone, and then leave the room knowing that the display automatically logs out of all accounts when the wireless connection is severed.

“It’s hard to overstate the value of standardized solutions for our students, faculty and district as a whole,” Marzec says. “Running a school or district involves a lot of moving parts, and when we have teachers who may use multiple classrooms or even multiple buildings throughout a day or a week, giving them the same tools everywhere ensures there’s no time lost sorting out technical issues or troubleshooting compatibility with their prepared lessons. The same is true for today’s students who have never known a world without touchscreens. With a streamlined experience year after year, they can become fairly advanced users of the LG CreateBoard technology throughout their education, helping develop explicit technical skills alongside the school’s curriculum.”

With LG CreateBoards, teachers can easily augment lessons with presentations or videos, screen share lessons or content from their own devices and enable students to screen share projects from their devices. With the new centralized control capabilities, Jamestown Public Schools can also easily deliver video morning announcements to every room without any action required from teachers. Lessons can be saved and stored online for later viewing and study, including live annotations over text or video that enable teachers to provide context, information or discussion to delve further than standard textbook descriptions or pre-prepared content.

LG CreateBoards Enhance Teaching

According to Jason Hubbard, senior account manager for education at LG Business Solutions, implementing CreateBoards can also fundamentally change how teachers approach the classroom by freeing them to leave their desk when using digital resources.

“The two-way connection between laptops and the LG CreateBoard means that they can control and manipulate their computer or content from the CreateBoard, unlike a projection system or other non-smart solution where they have to be at the desk to exert control,” says Hubbard. “This offers educators greater freedom of movement and caters to a variety of teaching styles, which can aid engagement and attentiveness, directly affecting student and school outcomes.”

When consulting Mercury Networks, the district considered different manufacturers and options, landing on the LG CreateBoard solution based on capabilities, manufacturer support and cost. The upgrade project began with 10 initial installations at the high school, then an expansion to five schools, and then the final decision to outfit every classroom all at once ahead of the 2024-2025 school year. Each room’s audio solution is also being upgraded to provide better sound quality and ensure long-term consistency for all users.

“We are excited to see our teachers and students leverage these technologies for greater collaboration and enhanced discussions in a way that encourages participation and connects with students’ daily experiences and digital lifestyles,” Marzec adds. “Additionally, buying into LG’s ecosystem has offered us new opportunities to consider deploying connected digital signage displays in hallways, cafeterias, entrances and other public spaces to provide school messaging or community content such as student achievement reels or replays of events including sports, performances, guest speeches and extracurricular activities.”

Marzec also noted how LG’s attention to detail and willingness to provide assistance went above and beyond his expectations. In the past, technology providers had been much more hands-off, while LG acted more like a partner in terms of working to answer questions, resolve issues and ensure the district was fully satisfied with the outcome. The last installations concluded in early July 2024, with every classroom at every school ready to launch for the fall semester.

Another version of this article originally appeared on our sister-site Commercial Integrator on October 21, 2024. It has since been updated for My TechDecisions’ audience.

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Technology has been a passion of mine for a long time, so I have personally found it fascinating to watch the variety of opinions and perspectives unfold as technologies mature. It has challenged my thinking and preconceptions, and I recognize that as a leader and a human I need to address them.

I’ve covered everything from fundamental ethics and whether it is good or bad, through to more specific considerations like ‘what do I want from AI?’, and therefore ‘what might others want from it?’.

Naturally, it’s been hotly debated by my colleagues. The leadership team is considering how today’s and tomorrow’s versions of AI should shape our own role in AI creation and adoption.

We already know that artificial intelligence for IT operations (AIOps) is poised to take advantage of the benefits. At Avantra, we’ve long evangelized the value of automation to offset risk, better utilize skill and boost productivity and innovation. But the debate that surrounds AI has helped us understand that our next phase of technical development must be underpinned with even greater pragmatism and responsibility.

The latest numbers I saw suggest that every day, 100 million people are experimenting with the likes of ChatGPT and other Large Language Models (LLM), such as Bard. Numbers like this highlight the popularity and allure that machines still have. Just like the washing machine, if it makes life easier, why would you not use it?

Download: ChatGPT and Generative AI in the Workplace

Proceeding with Caution

However, even though world renowned university colleges are condoning the use of conversational AI tools, leading experts are urging caution — legalities, politics, economics and ethics are top of the list of concerns.

It was eloquently summed up by The Future Life Institute, which is made up of over 1,000 experts, in an open letter asking the industry to pause AI development, or risk humanity and society. LLMs are learning so much so fast, that we, as a species, haven’t had time to truly process the long term impact. Ethics are at stake.

Taking Responsibility is Urgent

I think it’s a responsible challenge. As I said before the headlines have provoked my own thinking to evolve and prompted me to consider whether such a warning could, should or even will stop our own industry from forging on.

This is where I think the application of AI must be balanced against the dilemma. Take the example of producing project documentation or new product technical summaries. Is using ChatGPT to create the first draft irresponsible or a boon for productivity, freeing up time for innovation in other areas? Similarly, with the introduction of ‘copilot’ tools, like Microsoft assistant, people can increase their productivity and have more time for other things, even just going to the gym. I can see how it could make a sustainable argument for a four day week and happier colleagues.

Can Conversational AI Help Our Industry?

Of course, in my world, the real advantage of introducing ML and AI is the ability to help customers find answers to the problems they face. Using conversational AI to mine a database of known and defined errors other businesses have encountered — be that on SAP or Google — would help practitioners arrive at answers far sooner and avoid a degradation in productivity.

The process would augment the value of the intelligence we aggregate and own and, as it’s a trusted source, accelerate decision making and the time to resolution (TTR). No human can realistically (nor would they want to) hold in their brain all the common problem scenarios and fixes.

I’ve tried to do this in my professional career, and though possible, it is exhausting. That’s why I believe, applying conversational AI to the common challenges our customers face would help highly qualified and skilled humans validate and implement the decisions they take.

I’d advocate that automating the interrogation of vast knowledge banks makes complete sense, especially when it helps skilled people get on with doing what they do best — running, managing, and developing world class ERP.

I should be clear that I am wedded to the notion that it’s important the wider industry runs the AI race in tandem with the ethics that protect humanity. We must thoroughly understand the implications at every point in development and put in place the checks, balances and regulation to ensure the values we hold dear are protected and enhanced, not obliterated.

In the world of AIOps there is real value to its adoption not least to ensure mission critical systems related to food supply or energy stay online. We must therefore consider the broad view of AI technology as well as our narrower domain. Only with a balanced view and appreciation of the accountability we assume as leaders, can we make the right choices.

John Appleby leads Avantra as the Chief Executive Officer. Before Avantra John served as the Global Head of DDM/HANA Center of Excellence at SAP and as the Global Head of SAP HANA solutions at Bluefin Solutions, subsequently acquired by Mindtree. John is a recognized thought leader in the SAP market and was part of SAP’s Mentors Group. John holds an MA in computer science from the University of Cambridge.

The post Does Conversational AI Have A Role to Play in AIOps? appeared first on My TechDecisions.

The company says these improvements have improved Bard’s accuracy to computation-based word and math problems by 30%.

According to Google, the company is introducing a new technique called “implicit code execution” to help Bard detect computational prompts and run code in the background. The intended result is a more accurate response to mathematical tasks, coding questions and string manipulation prompts. These improvements also come with a new features that allows users to export a table to Google Sheets.

In a blog, Google leaders overseeing Bard say the improvements will make the generative AI chatbot better at answering questions such as:

• What are the prime factors of 15683615?
• Calculate the growth rate of my savings
• Reverse the word “Lollipop” for me

In the blog, Google says large language models (LLMs) are like prediction engines. Essentially, LLMs generate a response to prompts by predicting what words are likely to come next.

“As a result, they’ve been extremely capable on language and creative tasks, but weaker in areas like reasoning and math,” write Google Bard leaders. “In order to help solve more complex problems with advanced reasoning and logic capabilities, relying solely on LLM output isn’t enough.”

This new method, however, allows Bard to generate and execute code to boost its reasoning and math abilities.

According to Google, this approach is inspired from “a well-studied dichotomy in human intelligence, notably covered in Daniel Kahneman’s book “Thinking, Fast and Slow” — the separation of “System 1” and “System 2” thinking.

“System 1 thinking is fast, intuitive and effortless,” the Bard experts write. “When a jazz musician improvises on the spot or a touch-typer thinks about a word and watches it appear on the screen, they’re using System 1 thinking. System 2 thinking, by contrast, is slow, deliberate and effortful. When you’re carrying out long division or learning how to play an instrument, you’re using System 2.”

LLMs have been essentially operating under System 1, producing responses quickly but without deep thought, leading to some issues like trying to solve complex math problems.

Meanwhile, traditional computation more closely aligns with System 2 thinking as it is formulaic and flexible, but can produce impressive results with the “right sequence of steps,” Google says.

With the latest update, Google is combining the capabilities of both LLMs and traditional code – which it compared to combining System 1 and System 2 thinking.

“Through implicit code execution, Bard identifies prompts that might benefit from logical code, writes it “under the hood,” executes it and uses the result to generate a more accurate response,” Google says. “So far, we’ve seen this method improve the accuracy of Bard’s responses to computation-based word and math problems in our internal challenge datasets by approximately 30%.”

The post Google: Bard Now 30% Better at Computation-Based Problems appeared first on My TechDecisions.

The announcement came during the company’s annual Google I/O developer conference at which Google also announced new features for its generative AI chatbot Bard. Duet AI appears to be Google’s version of Microsoft’s generative AI assistant in Microsoft 365 which it calls Copilot.

Duet AI in Gmail, Slides, Sheets

According to Google, Duet AI already works behind the scenes in Workplace to help users refine emails and documents, and the company is now bringing the experience to Gmail on mobile to help users draft responses on the go.

The company’s initial launch of mobile will be fast-followed by contextual assistance that allows users to create professional replies that automatically fill in names and other relevant information.

This is in addion to Duet AI, Google says a new “Help me write” feature will be rolling out that allows users to leverage generative AI to help them write emails by typing a prompt of what they want to create a full draft of an email.

In Slides, Duet AI will help users generate images with a few words and generate an original visual to help support the text on the slides.

In Google Sheets, Duet AI will help users analyze and act on data with automated data classification and the creation of custom plans, the company says.

Google says classification tools understand the context of data in a cell and can assign a label to it to help eliminate manual data entry.

Also included in Sheets is a new “help me organize” capability that automatically creates custom plans for tasks, projects or any activity users want to track or manage. All they have to do is describe what they want to accomplish and Sheets will generate a plan for them, Google says.

Duet AI in Google Docs

In Docs, Duet AI will help users write content and include smart chips for information like location and status, as well as variables for details that users want to customize such. This adds to the “@ mention” feature in Docs that allows users to stay focused and collaborate in the document.

In addition, Google says it is adding new languages and bringing more capabilities to help with proofreading, tone and style in a new proofread suggestion pane that offers suggestions.

Duet AI in Google Meet

Like how Microsoft plans to bring Copilot into Microsoft Teams, Google wants to weave Duet AI into Google Meet, starting with the ability to generate unique backgrounds for video calls.

Test these features in Google Labs

To help users and organizations test out these new tools, Google is launching the waitlist for Google Labs and offering a limited number of spots to try out new Ai features in Search, Workspace, Project Tailwind and MusicLM.

Learn more about Google Labs and those projects in this short blog post.

The post Duet AI is Google’s Answer to Microsoft 365 Copilot appeared first on My TechDecisions.

According to Google, the Mountain View, Calif.-based tech giant’s updates include expanding access to Bard, bringing new visual capabilities to its AI-powered chatbot Bard, improving the generative AI’s coding capabilities and adding new productivity integrations.

Google Expanding Bard access

Purportedly in response to ChatGPT and competitor Microsoft’s massive investment in OpenAI, Google announced its large language model-powered chatbot Bard in February and launched it in March in a preview. Now, the company is removing the waitlist and opening up Bard to over 180 countries and territories, with more coming soon, Google says.

New Google Bard visual tools

In addition to new languages, Google is soon adding new visual interactions to Bard that will allow users to ask questions and get images in response to help explain the text. Also, users can use images in their own prompts via a Google Lens integration that will allow Bard to analyze the photo and include analysis in its response.

Google Bard Developer tools

Based on feedback from developers, Google is also introducing new features designed to make Bard a better coding assistant. With coding one of the main use cases of these early days of generative AI, Google hopes to strengthen Bard’s capabilities with more precise source citations, a dark theme and “export” button.

New Google Bard integrations

According to Google, export actions allow users to take Bard’s email and document drafts and move them directly into Gmail and Docs, respectively.

Source citations are rolling out next week, and the “export” button is listed as “coming soon.” Meanwhile, dark theme is now available.

The company also says it is working on integrating popular Google tools such as Docs, Drive, Gmail, Maps and more directly into Bard, and is also adding integrations with third-party software from Adobe, Kayak, OpenTable, ZipRecruiter, Instacart and more.

The post Google Bard Updates: New Coding Features, Integrations appeared first on My TechDecisions.

“The need to deliver provable value to the organization at scale is driving these trends in D&A,” said Gareth Herschel, VP Analyst at Gartner, in a statement. “Chief data and analytics officers (CDAOs) and D&A leaders must engage with their organizations’ stakeholders to understand the best approach to drive D&A adoption. This means more and better analysis and insights, taking human psychology and values into account.”

Gartner analysts presented the top 10 D&A trends that business and IT leaders must engage and incorporate into their D&A strategy at the 2023 Gartner Data & Analytics Summit.

Trend 1: Value Optimization

Most D&A leaders struggle to articulate the value they deliver for the organization in business terms. To achieve value optimization from an organization’s data and artificial intelligence (AI) portfolio, specific competencies such as value storytelling, value stream analysis, investment ranking and measuring business outcomes are required. D&A leaders should build clear links between their projects and the organization’s mission-critical priorities.

Trend 2: Managing AI Risk

The growing use of AI has exposed companies to new risks such as ethical risks. Managing AI risks is not only about being compliant with regulations. Effective AI governance and responsible AI practices are also critical to building trust among stakeholders and catalyzing AI adoption and use.

Trend 3: Observability

Observability is a characteristic that allows the D&A system’s behavior to be understood and allows questions about their behavior to be answered.

“Observability enables organizations to reduce the time it takes to identify the root cause of performance-impacting problems and make timely, cost-effective business decisions using reliable and accurate data,” said Herschel. “D&A leaders need to evaluate data observability tools to understand the needs of the primary users and determine how the tools fit into the overall enterprise ecosystem.”

Trend 4: Data Sharing Is Essential

Data sharing includes sharing data both internally (between or among departments or across subsidiaries) and externally (between or among parties outside the ownership and control of your organization). Organizations can create “data as a product,” where D&A assets are prepared as a deliverable or shared product.

“Data sharing collaborations, including those external to an organization, increase data sharing value by adding reusable, previously created data assets,” said Kevin Gabbard, senior director, analyst at Gartner, in a statement. “Adopt a data fabric design to enable a single architecture for data sharing across heterogeneous internal and external data sources.”

Trend 5: D&A Sustainability

According to Gartner, it is not enough for D&A leaders to provide analysis and insights for enterprise ESG (environmental, social, and governance) projects. D&A leaders must optimize their own processes for sustainability improvement. D&A and AI practitioners are becoming more aware of their growing energy footprint. As a result, a variety of practices are emerging, such as the use of renewable energy by (cloud) data centers, the use of more energy-efficient hardware, and the usage of small data and other machine learning (ML) techniques.

Trend 6: Practical Data Fabric

Trend 7: Emergent AI

ChatGPT and generative AI are the vanguard of the coming emergent AI trend. Emergent AI will change how most companies operate in terms of scalability, versatility and adaptability. The next wave of AI will enable organizations to apply AI in situations where it is not feasible today, making AI ever more pervasive and valuable.

Trend 8: Converged and Composable Ecosystems

Converged D&A ecosystems design and deploy the D&A platform to operate and function cohesively through seamless integrations, governance and technical interoperability. An ecosystem’s composability is delivered by architecting, assembling and deploying configurable applications and services.

With the right architecture D&A systems can be more modular, adaptable and flexible to scale dynamically and be more streamlined to meet the growing and changing business needs and enable evolution as the business and operating environment inevitably change.

Trend 9: Consumers Become Creators

The percentage of time users spend in predefined dashboards will be replaced by conversational, dynamic and embedded user experiences that address specific content consumers’ point-in-time needs.

Organizations can expand the adoption and impact of analytics by giving content consumers easy to use automated and embedded insights and conversational experiences they need to become content creators.

Trend 10: Humans Remain the Key Decision Makers

Not every decision can or should be automated. D&A groups are explicitly addressing decision support and the human role in automated and augmented decision making.

“Efforts to drive decision automation without considering the human role in decisions will result in a data-driven organization without conscience or consistent purpose,” said Herschel. “Organizations’ data literacy programs need to emphasize combining data and analytics with human decision-making.”

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The post Gartner’s Top 10 Data & Analytics Trends for 2023 appeared first on My TechDecisions.

According to Google, Bard can now help users with programming and software development tasks, including code generation, debugging and code explanation. Bard can carry out those tasks for more than 20 programming languages, including C++, Go, Java, Javascript, Python and Typescript.

Users can also export Python code to Google Colab without having to copy and paste. Bard can also help with writing functions for Google sheets, the company says.

In addition to generating code, Bard can help explain code snippets to users, which can be helpful if they are new to programming or need additional support to understand what a block of code means.

Google’s generative AI tool can also help users debug code, even if it’s code that Bard wrote. Users can tell bard “this code doesn’t work, please fix it,” and Bard can help debug the code.

Like other generative AI models, Bard is now 100% accurate and may provide inaccurate responses, and that includes when it comes to coding, Google says. Users are urged to double-check Bard’s responses and test code for errors, bugs and vulnerabilities before relying on it.

“Despite these challenges, we believe Bard’s new capabilities can help you by offering new ways to write code, create test cases, or update APIs,” Google says in a blog.

Google adds that users can also ask Bard to make code faster or more efficient, or find error handling clauses the chatbot may have missed.

Google’s AI Bard Programming Languages to Generate Code 

According to Bard itself, these are the programming languages in which it can generate code:

• C++
• Go
• Java
• JavaScript
• Python
• TypeScript
• C
• C#
• R
• Swift
• Kotlin
• PHP
• HTML
• CSS
• SQL
• Bash
• Perl
• Ruby
• Lua
• Rust

“With new coding capabilities, we’re excited to apply generative AI to accelerate software development, inspire innovation, and help people solve complex engineering challenges,” the company says.

The post Google’s AI Bard Can Now Help Generate Code in 20 Languages appeared first on My TechDecisions.

Microsoft, Google and other enterprise computing providers are leading the charge in bringing generative AI to the workplace with Bing and Bard, respectively. However, many other tech firms are integrating ChatGPT creator OpenAI’s GPT-4 and other language models into their solutions to provide an intelligent assistant to augment their human users’ skills.

With these tools and use cases rapidly expanding, enterprise IT leaders should begin thinking about potential use cases and developing a plan to bring ChatGPT and other generative AI models to their workplace, experts say.

This latest release of the TechDecisions Blueprint Series explores the new phenomenon and how IT leaders should go about deploying generative AI in their organizations.

In this whitepaper, IT leaders will learn about:

• • The emergence of generative AI
  • Enterprise use cases of generative AI
  • Security, privacy and ethics concerns of generative AI
  • How to deploy generative AI tools in your organization

Download our free guide now to learn more about enterprise applications, use cases and concerns with ChatGPT and generative AI!

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Microsoft and Google, two the biggest players in enterprise computing, are leading the charge in bringing generative AI to the workplace with Bing and Bard, respectively. However, many other tech firms are integrating OpenAI’s GPT-4 and other language models into their solutions to provide an intelligent assistant to augment their human users’ skills.

With these tools and use cases rapidly expanding, IT leaders should begin thinking about potential use cases and developing a plan to bring generative AI to their workplace, according to two Gartner analysts during a virtual press briefing on AI from the analyst firm’s Data & Analytics Summit this week in Orlando, Fla.

Generative AI is coming for the enterprise

According to Frances Karamouzis, the group chief of research for IT leaders and GTP, and a distinguished vice president analyst at Gartner, AI already exists in a wide range of enterprise tools either in the user interface or in the functionality, so enterprise IT leaders should not shy away from adopting new generative AI tools.

While there are data privacy and security risks, as well as ethical considerations, Karamouzis says enterprises simply cannot afford to be behind the curve on AI.

“The biggest risk is standing still,” Karamouzis says.

ChatGPT beat out the largest social media platforms and other popular consumer apps for reaching 1 million users first, achieving the feat in just five days. And, the chatbot is widely available and easy to use on OpenAI’s website, making it accessible to the masses.

Microsoft and Google are following similar footsteps, with Microsoft making their OpenAI-powered Bing Chat available in a preview, and Google beginning to do the same with Bard. The big tech firms are poised to compete with one another in AI for the foreseeable future, and others will inevitably follow.

That is leading Gartner to predict that by 2026, 100 million workers will have what the firm calls a “robo-colleague,” a synthetic virtual assistant designed to help make users more productive and efficient. Rather than replacing jobs, Karamouzis says there will instead be an evolution where workers use these AI tools to augment their decision-making.

“Will they replace jobs? No, but I think there will be incredible tools that will help recalibrate and redefine how we do work,” Karamouzis says.

The concerns with adopting generative AI in the enterprise

With this pace of innovation and an equal amount of intrigue from organizations and users, the vendor landscape has shifted to focus on AI and finding ways to bring the technology to customers.

Now, the question becomes how enterprises and IT leaders put the technology to good use. However, Karamouzis says that may be easier said than done, predicting that less over the next two years, less than 15% of enterprises are doing to derive meaningful value from it generative AI.

One of those roadblocks may be the ethical, legal and regulatory concerns over the use of these advanced AI models, says Svetlana Sicular, a vice president analyst at Gartner focused on data and AI.

Many regulations exist that govern the use of data, but Sicular anticipates much more red tape around the use of data in AI models. In fact, many such regulations are already in draft form, and regulators everywhere are well aware of these new AI capabilities.

Around ethics, there are serious concerns around plagiarism and essentially, if ChatGPT should be an author or not. Whether or not organizations should disclose that content was created by generative AI is a big question.

Other concerns around data security may be less obvious, but represent an area where enterprise IT leaders may want to approach with great caution, Sicular says.

“If you go directly to the link to ChatGPT, your data is their data,” the AI researcher and analyst says. “Their training their model on your data, and people don’t realize it.”

With enterprises intrigued about the possible use cases of these advanced AI tools, they should think carefully about creating guidelines. However, what keeps Sicular thinking positively about the adoption of generative AI is that these concerns are being raised at the forefront of its emergence rather than after adoption is already widespread.

Sicular compares this to the emergence of social media, for which IT leaders and enterprises were not totally prepared.

“The alarms for AI were raised earlier in the cycle than for social media, which gives me hope that we will do the right thing,” Sicular says.

Enterprise adoption of generative AI and ChatGPT

As with any other emerging or trending technology, enterprises should remain open to the possible use cases and do their due diligence on how best to deploy generative AI models and intelligent virtual assistants.

Sicular suggests simply letting technology leaders explore its capabilities and use cases, but doing so safely and securely.

Coding has emerged as a popular early use case of generative AI, with programmers using these tools to generate code that is then quality checked by human experts. The human control of these programs, Sicular says, is key.

Microsoft has adopted the term “copilot” for its OpenAI integrations across its products, and that is a framing that bodes well for the industry, Sicular says.

“I like the name copilot. It reflects that you’re in charge,” Sicular says. “You’re asking someone trusted to help your or take on some of your tasks and give you the result of those tasks.”

Sicular also recommends that organizations have an open discussion about the possible use cases, encouraging users to share their experiences and allow use cases to grow organically based on that success.

“That’s where use cases will surface,” Sicular says. “It will take time for the enterprise to find those use cases, but if you allow people to experiment, you will see some interesting ideas that will make enterprises competitive or help them do certain things in a new way.”

The post IT Leaders Should Prepare for Generative AI in the Enterprise appeared first on My TechDecisions.

In a blog post, the company says it is starting to open access to Bard, a chatbot powered by a research large language model (LLM) and an optimized version of LaMDA, the company’s conversational AI technology. However, Google says it will update Bard with newer, more capable models over time.

According to Google, Bard is similar to other chatbots in that it is not always entirely accurate and has some limitations, but notes its “incredible benefits” such as assisting and facilitating productivity, creativity and curiosity.

When using Bard, users will often get multiple different drafts of responses from which to start. Users can continue to collaborate with Bard from there, including asking follow-up questions. Users can also simply ask Bard again for an alternative answer.

Similar to the new Microsoft Bing and its chat feature, Google calls bard a “direct interface to an LLM” and as a “complementary experience to Google Search.” Bard is designed so users can easily visit Search to check its responses or explore sources from across the web.

There will also be a “Google it” button to see suggestions for queries, and Search will open in a new tab so users can find relevant results and dig deeper, the company says.

“We’ll also be thoughtfully integrating LLMs into Search in a deeper way — more to come,” Google executives write in the blog, hinting at a potential chat component to Google Search, similar to how Microsoft integrated OpenAI’s newer ChatGPT model GPT-4 into Bing.

Google says it will continue to improve Bard and add new capabilities, including coding, more languages and multimodal experiences.

The launching of Bard comes more than a month after the company first announced Bard and when it fist began making Bard available to “trusted testers.”

In a blog post announcing Bard last month, Google CEO Sundar Pichai said external feedback will be combined with the company’s own internal testing to improve Bard and ensure quality and safety in real-world information.

The company’s chief executive detailed the company’s history of using AI to improve Google Search, including BERT, one of the company’s first Transformer models, and then MUM, which is 1,000 times more powerful than BERT.

“Now, our newest AI technologies — like LaMDA, PaLM, Imagen and MusicLM — are building on this, creating entirely new ways to engage with information, from language and images to video and audio,” Pichai says.

Google will now begin bringing these AI advancements to the users of its products, beginning with Search, Pichai writes.

Google’s announcement also comes the same day as Microsoft announced Image Creator in Bing, a new image generator running on an advanced version of OpenAI’s DALL-E.

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