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STACK’s proven design supports the next generation of data centers and their artificial intelligence workload requirements

STACK Infrastructure (“STACK”), the digital infrastructure partner to the world’s most innovative companies and a leading global developer and operator of data centers, positions itself as the premier developer for the future era of data centers, leveraging its established AI-Ready capabilities built upon STACK’s proven, customizable design. With a history of supporting high-density workloads, STACK reinforces its position as a pioneering partner to the world’s foremost technology providers.

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In the rapidly evolving landscape of technology, characterized by generational advancements in AI, the demand for data center capacity capable of accommodating high-density workloads is reaching unprecedented levels. A prime example is OpenAI’s ChatGPT, the generative AI chatbot launched just over a year ago and, within two months, became the fastest-growing consumer application in history. With such remarkable growth of AI and other machine learning applications, STACK’s cutting-edge data center solutions and its extensive portfolio of powered land holdings have become even more crucial to today’s technology companies. Purposefully crafted to meet the escalating high-density requirements of clients, STACK’s resources are positioned at the forefront of innovation.

“STACK was built for the world’s largest innovators, and from the beginning, we have prioritized the long-term scalability of our clients with a flexible data center design,” said Matt VanderZanden, Chief Operating Officer of STACK Americas. “As an AI-Ready digital infrastructure company with a proven track record of high-density deployments, STACK is building upon this foundation to continually address evolving client needs.”

STACK achieves optimal cooling for high-density AI workloads through its closed-loop water cooling systems, offering flexibility to meet diverse cooling requirements including customizable solutions that can support up to 30kW per rack with traditional air cooling; up to 50kW per rack with rear door heat exchangers; up to 100kW per rack with direct-to-chip liquid cooling; and up to and exceeding 300+kW per rack with immersion cooling in the future. STACK’s extensive portfolio of operating data centers, all designed based on cost-efficient and proven models, exemplifies its ability to swiftly deliver gigawatts of scale, coupled with expertise in cooling systems enabling greater and greater deployment densities, and affirms STACK as the ideal data center developer for sustained growth in the age of AI.

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STACK’s global footprint of campuses spans major data center markets across the Americas, EMEA, and APAC, offering a vast powered land portfolio, sustainable building solutions, and high-density cooling optionality for the next generation of AI-Ready data centers. With 2.5+GW built or under development and an additional 4.0+GW of planned and potential development, STACK strategically supports the hyperscale requirements and groundbreaking initiatives of leading global technology firms through the development of AI-Ready campus developments including:

• A planned five-building data center campus offering 250MW of scale in Central Phoenix with a dedicated on-site substation.
• A 48MW Santa Clara data center, featuring immediately available shell space powered by an onsite substation with rare contracted capacity.
• A 56MW Toronto campus, spanning 19 acres, includes an existing 8MW data center and 48MW expansion capacity, all supported by committed power.
• A 48MW build-to-suit opportunity in the Dallas/Fort-Worth area, boasting abundant power and connectivity options.
• A 200MW campus in Portland spanning 55 acres with 96MW currently available for leasing.
• A New Albany, Ohio 58MW data center campus with immediately available capacity and build-to-suit expansion opportunities.
• A strategically located data center campus in Osaka, Japan with 72MW of capacity across three planned buildings.
• A 36MW facility delivered in Australia, launching a 72MW campus in Melbourne, one of the fastest growing markets in Asia Pacific.
• A 30MW data center campus in Stockholm with 18MW under development.

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 [To share your insights with us, please write to sghosh@martechseries.com] 

The post Stacked Infrastructure Expands its AI-Ready Data Center Capabilities to Support Machine Learning appeared first on AiThority.

In their infancy, NFTs have suffered mightily from both misconceptions about the technology behind them and manipulation by fraudsters and hackers. Issues have arisen because many people, including creators, rushed to treat them as monetized cryptocurrency projects, tradable assets, and get-rich-fast investments. The more thoughtful, functional opportunities possible with them have often been overshadowed by hype, speculation, speed, and greed.

That’s finally starting to change — and it isn’t because brands made them collectibles or high-end coupons. It’s because evolving technical capabilities are steadily improving NFT functionality.

It’s still true that an NFT refers to an asset, most often an image, tokenized with a unique digital signature recorded on a decentralized, immutable blockchain like the Ethereum network. This signature on a distributed blockchain ledger, across thousands of computers worldwide, ensures that the NFT’s existence and transfer can be verified with an extremely high level of certainty — without relying on a central authority like a bank or broker. That’s well and good, but the public has largely remained unable to see this in practice, translate what it means, or find relevant applications to their lives and work.

With the emergence of programmable NFTs in 2023, we can now directly embed content and executable programs inside an NFT, which creates a significant difference in how we experience them, their utility, and even the jobs they can perform for us. My team’s new Immutable Miniverse Format (IMF), for example, immutably encodes — and can encrypt — tailored messages, games, music, binaries, and interactive experiences within an NFT, visualized as a string of secret code in motion. Importantly, this self-contained “miniverse” is embedded as part of the NFT artwork — without the technology burden of maintaining Web3 access points when being used on traditional social media.

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The Next Level with Generative AI

Fusing NFT art and programming code in a self-contained way is a significant development.

Programmable NFTs can be leveraged for work and play, shared on today’s social media platforms (Web2) and even serve as the building blocks of a kind of “app store” for Web3 and a more decentralized economy, comparable to today’s mobile phone apps. Additionally, the use cases in everyone’s mind involve generative AI technologies.

For good reason: the ultimate NFT utility may be the capacity to tokenize intelligence in a decentralized and immutable fashion.

Here, we’re not talking about using generative AI to churn out NFT art, rather the focus is on integrating LLM chat capabilities into programmable NFTs and ultimately empowering owners to program and mint their own NFTs to do this. My team is enabling NFT holders to have a private conversation with and within their NFT about the domain and knowledge embedded inside their NFT’s miniverse. This means leveraging a customized, fine-tuned version of an LLM, while not subjecting any input to third-party services that could opaquely use the data or violate privacy — a criticism leveled at OpenAI and others in a typical centralized GPT setting.

In fact, if you’re maximizing the strengths of both technologies, NFTs and gen AI, then:

• The embedded information on which an LLM conversation is based should be immutable, individualized, and decentralized.
• The conversation with such embedded information must preserve privacy. It does not need to reference any public GPT services.
• NFT creators must be committed to decentralized AI on Web3. Future iterations should and will allow a user to run their LLM model locally on the user’s own computer.

The protection of privacy possible with NFTs is a differentiator compared with using generative AI in a web application. A criticism of ChatGPT, BARD, and similar systems is that input from a user becomes data consumed by the generative AI, including proprietary input, and that can ultimately become available to other users. A generative tool like Microsoft’s Copilot stores input data, while assurances are made that it isn’t used for training large language models.

Still, the concern is that the power of massive data and its control becomes centralized even more by the hyperscaler giants of computing and the few smaller companies they back.

Blockchain’s fundamental decentralization and distribution means that generative AI NFTs can offer an alternative to that system of big data control.

Additionally, AI, as with mobile now, can leverage edge computing, not centralized cloud services.

Long-term Uses of Programmable NFTs in Life and Business

The viability of a technology depends on its ability to solve real problems and to create new possibilities and experiences beneficial to humanity and the world. Right now, we’re seeing a tremendous blooming of new uses for generative AI. When sharing information or when interaction needs to be secure, private, and impervious to short- or long-term systems failure or third-party dependency, the integration of NFTs and AI will prove especially handy.

In the personal realm, consider how you might preserve and interact with family history and important private documentation shared among family members over the long term, without pieces of that being scattered or permanently lost. Some families have members who live across the world and with whom they want to share information. Most people have family members dear to them who have passed away or will do so. Imagine an interactive record of your grandparents’ lives — one that you can have a conversation with. Imagine documenting family events from yesterday, five years ago, or fifty years ago that are less likely to be lost to time in a decentralized system. With programmable, AI-capable NFTs, you and your specified family members can own the assets with the data, the knowledge, the documents, and the interactive capabilities, as long as you have an internet connection. Digital existence and private access are distributed and not dependent on permission granted by a central authority or third party.

The same principles hold true for business uses.

Consider proprietary documentation, blueprints, and even trade secrets that need to be shared among specific engineers across a global workforce or from an older generation to a newer one within a company.

With an NFT, you could securely encrypt documentation, share it with an intended party, and, with generative AI capabilities, enable them to ask questions of it — even, in a sense, converse with engineers retired or long gone. Questions and answers about the documentation can instantly be translated into other languages.

Because NFTs are immutable and recorded permanently in a distributed public registry, impervious to deletion or third-party tampering, their potential for authenticating products and verifying lineage in the supply chain has often been noted.

Adding a layer of interactive inquiry with embedded generative AI makes this business use case even more exciting.

A programmable NFT or immutable “miniverse” with generative AI functionality is a new frontier in interactive, customized applications for personal and business use that truly puts ownership in individual hands. It’s time to lift NFTs out of the abyss of financial speculation and esoteric understanding and put the spotlight on their technical capabilities — which can make them useful for everyone.

[To share your insights with us, please write to sghosh@martechseries.com]

The post Generative AI Inside Programmable NFTs Is New — and Can Accelerate the Sector Beyond Hype appeared first on AiThority.

IPFone Unveils The ChatGPT-Enabled ‘IPFoneMate’ for Enhanced Webex Interactions

IPFone a pioneer in cloud communication services, is excited to announce the launch of “IPFoneMate,” the first Webex bot fully integrated with OpenAI’s ChatGPT. This groundbreaking tool leverages OpenAI’s ChatGPT technology, tailor-made to support organizations of various sizes in managing essential customer support, troubleshooting, and training tasks. IPFoneMate sets a new benchmark in customer service quality and significantly improves the customer experience.

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The OpenAI/ChatGPT bot is specifically customized for each business or industry, drawing on the company’s own resources such as learning centers, manuals, presentations, sales collateral, and other relevant documentation.

Key Applications:

• Customer Support: Equipped to deliver prompt and accurate responses to customer queries, the bot ensures high-quality and efficient customer service.
• Advanced Troubleshooting: IPFoneMate adeptly identifies and addresses common issues, providing detailed guidance and support.
• Employee Training: The bot offers comprehensive training on the latest products and services tailored to specific industries or companies.

“Integrating AI-driven solutions like ChatGPT with Webex can provide businesses with a significant competitive advantage. This integration enhances communication and support for customers and clients, particularly by offering instantaneous responses to inquiries, thereby significantly enhancing the customer experience,” stated Damian Chmielewski, CEO of IPFone.

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The introduction of IPFoneMate is a testament to IPFone’s ongoing commitment to innovation in cloud communications. This includes services such as UCaaS, Webex, Contact Center, Internet, SD-WAN, and more. With over 25 years of industry experience, IPFone continues to lead in offering advanced solutions to meet contemporary business challenges.

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 [To share your insights with us, please write to sghosh@martechseries.com] 

The post IPFone Introduces “IPFoneMate”: A New Era in Customer Assistance with ChatGPT Bot for Webex appeared first on AiThority.

MyHeritage, the leading global family history service, announced  the release of two groundbreaking features that mark the next frontier in family history research: AI Record Finder and AI Biographer. AI Record Finder revolutionizes genealogy like ChatGPT revolutionized searching the internet: it is an interactive, intelligent, free-text chat to help the user locate relevant historical records about a person of interest in MyHeritage’s vast database of 20 billion records. AI Biographer automatically compiles a rich narrative about an individual’s life using information from historical records that match the person, creating a Wikipedia-like biography about anyone. Narratives are enriched with relevant historical context using AI and are easy to share. MyHeritage is the only service to offer such groundbreaking features for family history, and the first to leverage conversational AI for searching historical records. The two features are integrated, allowing users to generate an AI Biography™ for individuals they find using AI Record Finder. AI Biographies may also be generated directly for individuals in family trees on MyHeritage.

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“We’re constantly pushing the boundaries of genealogy to reinvent the way people can discover their family history as we implement a bold vision for genealogy in the 21^st century”

AI Record Finder

Until now, searching for historical records on online genealogy platforms like MyHeritage has been very similar to using a regular internet search engine. One entered names and other terms into dedicated fields in a search form, and the search engine returned a large number of search results. Then, it was necessary to comb through the results to discover relevant information. AI Record Finder transforms this experience by enabling users to converse with an AI assistant in a chat to quickly find records about their ancestors, relatives, or other deceased individuals. Users can still use the traditional search engine on MyHeritage, but AI Record Finder™ adds an additional chat mode that increases the chances that users may be able to find elusive records they have never found before, thanks to the power of AI.

The chat is like an interview with a friendly concierge that the user can converse with in one of two modes: casual or formal. AI Record Finder processes the information the user enters, and understands what additional details are necessary to help narrow down the search results. It guides the user by asking the relevant questions according to the context and information provided by the user, to find the most relevant records about the person the user is searching for. Once located, the records can be reviewed and the details saved to the user’s family tree. AI Record Finder™ includes a seamless user interface, where historical records that are found appear directly within the chat.

AI Biographer

AI Biographer™ creates a rich Wikipedia-like biography summarizing a person’s life. This is especially useful for creating biographies about the billions of individuals who were not famous, and therefore do not appear in Wikipedia. An AI Biography can be created from historical records found via AI Record Finder™ and for deceased individuals within a user’s family tree on MyHeritage. AI Biographer utilizes MyHeritage’s acclaimed matching technologies to curate historical records and family tree profiles that pertain to the selected individual. All information from the pertinent records is then compiled into an biography that is enriched with photos and scanned documents, and in some cases, additional information from the web. The resulting biography includes the person’s immediate family, describes the main events of their life, and includes rich historical context and the origins of their surname. Each biography is a unique narrative that can be shared with family and friends, and saved for posterity. Facts listed in AI Biographies include footnotes and source citations, and link to the records from which they were obtained. Any inconsistencies within the information listed are noted. AI Biographies are saved as PDF files that are emailed to the user.

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When created from the user’s family tree, an AI Biography is added to the family tree as a media item and tagged with the individual’s name, so that it is accessible through the MyHeritage mobile app and Family Tree Builder desktop software. The biography is included whenever the family tree is exported in GEDCOM format, ensuring that the enriched biographical information remains an integral part of the family tree. Biographies can easily be regenerated whenever new information becomes available. Additional entry points for generating an AI Biography such as from MyHeritage’s traditional form-based search engine, and from family tree profile pages, will be added soon.

“We’re constantly pushing the boundaries of genealogy to reinvent the way people can discover their family history as we implement a bold vision for genealogy in the 21^st century,” said Gilad Japhet, Founder and CEO of MyHeritage. “AI Record Finder is a disruptive feature that simplifies the way people can find information about their ancestors by making the search easier and more intuitive. AI Biographer curates the details about a person’s life into a compelling story. Not all our ancestors were famous, but they all deserve to be remembered! Together, these cutting-edge features strengthen MyHeritage’s position as the industry leader for innovative genealogy and continue our mission to make family history easier, more accessible, and more fun for everyone.”

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[To share your insights with us, please write to sghosh@martechseries.com]

The post The MyHeritage AI Record Finder and AI Biographer Transform Genealogy with Artificial Intelligence appeared first on AiThority.

UST, a leading digital transformation solutions company, has introduced UST AlphaAI, which consolidates the company’s comprehensive suite of Artificial Intelligence (AI) services, solutions, and platforms. The introduction of UST AlphaAI strategically positions the company for further success in the dynamic AI landscape. It seamlessly combines UST’s technical expertise, domain knowledge, and real-world experience to provide its clients and partners with effortless access to UST’s full spectrum of transformative AI solutions, unlocking new business efficiencies and fostering sustainable transformation. UST AlphaAI enhances businesses’ agility and competitiveness, streamlining operations and accelerating their journey toward excellence.

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Drawing on a rich history of collaboration with distinguished AI researchers from top academic institutions such as the MIT Computer Science & Artificial Intelligence Laboratory and the Stanford Artificial Intelligence Laboratory, UST has a reputation for expertise and excellence at the forefront of AI innovation. This unique blend of practical experience and academic expertise gives UST the flexibility needed to swiftly respond to emerging market demands. With the introduction of UST AlphaAI, UST will further augment its capabilities by merging academic insights with real-world expertise.

A leader in AI innovation, UST has successfully delivered over 100 AI implementations. Some of the successful implementations of UST AI solutions include:

• A computer vision-based loss prevention solution for a major retailer that reduced checkout theft and increased the annual revenue per store by $50,000 – $70,000.
• An intelligent retrieval system utilizing natural language processing (NLP) and Deep Learning for a financial services company, increased marketing, and content creation team productivity by 85%.
• A generative AI-based code modernization initiative to increase developer productivity for a large CPG company which compressed software development timeline by 35% while improving code quality and test coverage.
• Operationalization of MLOps and LLMOps with AI guardrails for a UK-based financial institution, reducing their model development, deployment, and testing time by half.

UST SmartOps and UST Sentry Vision AI are just two examples of how UST is exploiting the boundless potential of AI. UST SmartOps, an intelligent automation platform, leverages the power of Generative AI to provide intelligent document insight, seamless incident handling, and automated process creation. UST Sentry Vision AI, a groundbreaking solution, seamlessly integrates with SAP S/4HANA to optimize operations, automate processes, and maintain quality for CPG and manufacturing clients. This intelligent, vision-based monitoring and process adherence tool minimizes operational waste and enhances digital enterprises.

“At UST, we work to understand the specific needs of our clients. We believe that applying the right AI solutions to the right problems in the right way delivers the best possible business outcomes. UST is committed to sustained growth in this dynamic market segment, and our partnerships with leading AI research institutions ensure we remain at the forefront of innovation as well as the ability to continue applying these breakthroughs through pragmatic, real-world solutions,” said Manu Gopinath, Chief Operating Officer, UST.

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“Our extensive experience at the forefront of AI innovation has enabled UST to respond quickly to client needs and build bespoke solutions for clients and partners. By applying the latest advances in AI to our clients’ business problems, we can create end-to-end solutions that enhance business outcomes by accelerating change, driving efficiency, and elevating user experiences. UST AlphaAI accelerators will elevate our ability to respond to rapidly growing generative AI demands as we continue working to shape the emerging enterprise AI landscape,” said Dr. Adnan Masood, Chief AI Architect, UST.

Numerous products, platforms and implementation accelerators offered by UST AlphaAI were showcased at UST’s recent annual global D3 conference and Expo held in India. The conference underscored UST’s commitment to pioneering generative AI and reaffirmed AI’s role as a transformative technology and an agent of growth.

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[To share your insights with us, please write to sghosh@martechseries.com]

The post UST Introduces UST AlphaAI, Solidifying its Leadership Role at the Forefront of AI Innovation appeared first on AiThority.

With barely a few days left in 2023, I am offering my views on the adoption and impact of generative AI in legal industry in 2024, in the context of the knowledge management function.

Generative AI will deliver value to those who know how to use it, the tool doesn’t understand your legal function

Whilst generative AI is becoming synonymous with AI, the reality is that the latter isn’t a single technology but a cluster of different technologies. Generative AI applications, on the other hand, specifically use natural language processing on data provided to deliver results and outcomes in response to precise requests. The generative AI application doesn’t understand the legal concepts underlying the questions that it is asked or the words/output that it produces. So, legal expertise within the context of matter strategy and complexity is needed to sanity-check the outputs the generative AI tool throws up.

Consequently, generative AI will deliver value and convenience only to those who know how to use it, and even help fine-tune thought processes to achieve the desired outcome. For instance, the same question can be asked in multiple ways, and generative AI will respond in different ways. Likewise, lawyers can receive different outputs to the same questions, depending on the documents that they are ‘authorized’ to access in the firm. The tool is processing natural language, after all!

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Microsoft will enable generative AI adoption, but compliance and confidentiality will be showstoppers

In the near term, the first ‘showstopper’ for meaningful use of generative AI will be compliance.  A lawyer using generative AI (be that co-pilot or its adaptive version) to create a report for sharing with clients or third parties needs to ensure that the document complies with all the applicable data protection and data privacy regulations. In addition to enabling generative AI adoption through the provision of a co-pilot, Microsoft will play a role in ensuring that data security and residency aren’t compromised.

Microsoft’s security policy for Azure ensures that data residing in individual organizations’ cloud tenants is not shared externally.

So, it will be incumbent on law firms to only use data that is within their own cloud tenant, much like it was in previous years where data resided within firms’ networks.

The second showstopper is going to be data confidentiality. At an individual user level, people will only have access to documents they are authorized to view, based on the principles of need-to-know security. This means that individuals using the firm’s generative AI tool will only surface results based on the data they are authorized to access. In some cases, the tool may produce output based on a completely different set of documents to another individual. This will possibly impact the value of generative AI in terms of contextual accuracy, currentness, and suitability.

Without a trusted knowledge source, your generative AI tool will deliver limited value

Document management systems will be the logical place for law firms to embark on their AI journey, which, BTW for many firms, have already started.

For instance, AI tools are embedded in document management systems to assist with document classification, automatic filing of emails and documents based on user behaviors, and even interrogating the application for information by asking specific questions. Note here that for this kind of broad AI adoption, there is no need to “train” the tool for it to deliver the desired results.

To adopt generative AI and ensure that the tool is “trained” on the most accurate, authorized, and current data, firms will need to create a central, curated repository of trusted data – i.e., the knowledge management system. This will ensure the best and most useful output. To illustrate, a lawyer would be able to instruct the firm’s generative AI tool to create an 800 words abstract based on a 100-page M&A contract, that refers to participants from the US and Germany and pertains to the New York jurisdiction – and be assured that the right data has been used to create the output.

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It isn’t the ‘rise of the machine’ in legal

Finally, despite the hype surrounding generative AI, we aren’t heading towards a ‘rise of the machine’ scenario in legal. There are many issues to iron out – from hallucinations and security to ethics, data management, and regulation – which means that human intellect is very much indispensable. It’s true that AI technology more broadly has a lot to offer in the form of support, convenience, and efficiency – and that over time generative AI will become more accurate. But natural language processing is exactly that – i.e., language processing. Generative AI engines know what letters or words to put one after the other, but it does not understand the words or concepts and needs detailed instruction and high-quality data to deliver value.

[To share your insights with us, please write to sghosh@martechseries.com]

The post A Trusted ‘Knowledge’ Repository is Key to Generative AI Adoption in 2024 appeared first on AiThority.

SnapLogic Chief Scientist Greg Benson reveals his predictions on Generative AI, and the challenges and opportunities it presents in 2024.

Prediction 1 – GenAI won’t take your job, but it might change it.

In 2024, Generative AI won’t lead to mass job displacements and redundancies, as many early sensationalist reports might have suggested. GenAI won’t completely replace experts in any field, as although models have access to an insurmountable amount of information, users still have to articulate concepts well enough to get the right answers – thus, expertise and human input and, more importantly, human review always will be necessary.

Collaboration with GenAI is a trend we can expect to continue in 2024, as businesses look to capitalize even further on its benefits, reaping the rewards of increased productivity and quality of content creation. This means adopting even more GenAI tools and encouraging even more use of them; the goal being not to replace workers, but instead assist what they do.

Prediction 2 – Now that we’ve invented GenAI, the next step is understanding it.

Next year, we can expect to see businesses attempt to improve the consistency of output from Generative AI. Currently, there is no set rule book for achieving great results with GenAI; there are tips and tricks you can deploy for better or faster results, of course, but overall the process is largely trial and error.

Interacting with GenAI in its current iteration is like a science experiment – you come up with a hypothesis and continue to test different manners of prompts until it produces the result you’re looking for. In the future, the focus of experimentation will be on figuring out how we evaluate the responses it gives us and using that data to inform prompts further.

Companies that want to apply GenAI to their products will need to think about how they carry forward and evolve prompts that can improve results directly. Qualitative and quantitative improvements can only be brought about by reevaluating their approach to AI application and development.

Prediction 3 –Expect an onslaught of GenAI tools and GenAI startups.

In 2024, we’re going to see another year of the AI market expanding, with more variety as GenAI startups try to find their niche among the masses.

Rather than consolidation, more GenAI solutions will continue to pop up in different industries. Of course, there will be a lot of attempts that don’t get traction, or just don’t work, but this won’t deter the wave of opportunistic entrepreneurs and businesses who look to capitalize on the GenAI wave.

There’s already the start of a huge race on the hardware side too: companies such as Google and AWS are building their own AI hardware in addition to NVIDIA, which is worth watching. If successful, these advances in hardware could lead to another explosion in how large language models are trained, as currently, it takes a lot of human input, money, and effort to build from the ground up.

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Prediction 4 – GenAI regulation is essential to adoption.

Regulating GenAI will be a huge focus for governing bodies and business leaders in 2024. Earlier this year, calls were heard for a pause in AI development from numerous visionaries, but this isn’t realistic as the fundamental technology is increasingly available through open-source models available on Hugging Face. Rather than focusing on halting development, creating clear regulations, guidelines and best-use practices will be necessary to ensure partnership with AI will move forward safely and securely.

Like any other technology, defining the boundaries that keep safety in mind will allow for leveraging the benefits without sacrificing progress. We can liken this to all manners of tools and equipment that need to be regulated; for example, we don’t stop ourselves from building cars that go fast, but we do put speed limits in place to ensure safety. Internationally, governments will draw their attention first to the areas of regulation that present the greatest impact on citizens, including frontier AI.

From an industry perspective, the GenAI applications and most helpful cases will emerge as front runners for wider business use cases. Understanding the risks, challenges, and security issues potentially imposed by these tools will be vital for businesses to understand exactly when and how these tools need to be regulated internally.

Likewise, companies hoping to leverage GenAI will have to communicate to customers exactly how it’s used and how it complies with current and future regulation requirements.

Prediction 5 – GenAI and Legacy technology: Why the key to modernization may reside in GenAI tools.

After a year of GenAI practice, legacy businesses are starting to understand that GenAI interest is not just driven by ‘hype’, and instead could be truly transformative for their sector. Therefore, in 2024, we can expect even more traditional businesses to deploy the technology to help evolve legacy systems and modernize their technology stack.

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Typically, traditional companies are not amenable to change or agile enough to adopt the latest in new technology. Many companies are tied to legacy software due to a combination of outdated procurement processes, familiarity, or concerns about data loss or disruption, making modernization inaccessible. The key here is that GenAI can assist with migrating off old code bases and technology stacks to modern programming languages and platforms.

However, GenAI could bridge this gap by allowing companies previously locked into legacy systems to access a more modern workforce’s knowledge and work practices. GenAI also makes some modern tools far more user-friendly, and therefore more likely to be deployed across businesses.

Prediction 6 – AI and the question of originality

Next year we’ll see the average person become more adept at using AI, both in business and in their personal lives. Students will also interact with GenAI at a greater scale.

On the one hand, ChatGPT and others can be great personal tutors to help students understand concepts. On the other hand, ChatGPT can be used to generate solutions to problems. I tell my students that they can use GenAI to help them as they are learning, but they must turn in their own original work. The problem is that it is extremely tempting to have GenAI provide the answers, perhaps just partially. In addition, since the answers are coming from a computer program and not another student, it distances students from the notion they are cheating. So far, for my classes in computer systems, it has been fairly easy to determine if a student has turned in GenAI solutions because they don’t follow the conventions in code that I’ve taught in class and require in student solutions.

How GenAI is used in classrooms is very much a work in progress. At the moment there’s still no best practice model – even at my University, we have workshops about AI, but no succinct policy. Beyond the classroom, there is the larger question of intellectual property and how GenAI is trained on internet-accessible creations and works available in digital form. We will see this play out in all industries and the courts in 2024.

Top AI ML Insights: NICUs And AI For Babies

Prediction 7 – Universities will begin to teach prompt engineering

In 2024, universities will teach prompt engineering as a minor field of study and through certificate programs. Prompt engineering for GenAI is a skill already augmenting domain experts, similar to how computing has augmented other domains. The successful use of large language models (LLMs) relies heavily on giving the models the right prompts. When looking to fill the role of a prompt engineer, the task becomes finding a domain expert who can formulate a question with examples in a specific domain, a skill critical for today’s IT

professionals to refine to successfully implement LLMs. Given this, universities will introduce new academic focus areas to address the growing demand for professionals with specific skills required to build the next generation of GenAI applications.

Currently, SnapLogic is the leader in generative integration. As a pioneer in AI-led integration, the SnapLogic Platform accelerates digital transformation across the enterprise and empowers everyone to integrate faster and easier.

Whether you are automating business processes, democratizing data, or delivering digital products and services, SnapLogic enables you to simplify your technology stack and take your enterprise further. Thousands of enterprises around the globe rely on SnapLogic to integrate, automate, and orchestrate the flow of data across their business.

[To share your insights with us, please write to sghosh@martechseries.com]

The post SnapLogic Chief Scientist Reveals GenAI Predictions for 2024 appeared first on AiThority.

Reserv, the innovative AI-driven insurance Third Party Administrator (TPA), is thrilled to welcome James Maddox, co-founder of Mya Systems, as its new CTO. With expertise in Machine Learning and Natural Language Processing, Maddox aims to revolutionize the adjuster experience by integrating Large Language Models and modern architecture. Reserv, having swiftly grown since exiting stealth mode in July 2022, operates globally with over 100 employees. Maddox’s role focuses on enhancing policyholder experiences through seamless, efficient services and delivering valuable insights to carriers and underwriters. CEO CJ Przybyl anticipates scalable operational efficiencies, positioning Reserv as a critical data hub in the insurance industry.

The post Reserv Hires Natural Language AI Expert James Maddox as Chief Technology Officer appeared first on AiThority.

Foresight, developer of the leading AI-enabled platform for helping owners and contractors complete major construction projects on time and on budget, is excited to announce the release of “Casey”, our new generative AI based helper. Casey is an easy to use and secure approach to creating guidance for proactive project execution.

The post Foresight Announces Generative AI Helper | Accelerate and De-risk Major Capital Projects With AI appeared first on AiThority.