AI Solves All Our Problems

Although AI can be quite useful, it seems that the promise of generative AI has lead to irrational exuberance on the topic. This episode of the Tech Field Day podcast, recorded ahead of AI Field Day, features Justin Warren, Alastair Cooke, Frederic van Haren, and Stephen Foskett considering the promises made about AI. Generative AI was so impressive that it escaped from the lab, being pushed into production before it was ready for use. We are still living with the repercussions of this decision on a daily basis, with AI assistants appearing everywhere. Many customers are already frustrated by these systems, leading to a rapid push-back against the universal use of LLM chatbots. One problem the widespread mis-use of AI has solved already is the search for a driver of computer hardware and software sales, though this already seems to be wearing off. But once we take stock of the huge variety of tools being created, it is likely that we will have many useful new technologies to apply.

https://youtu.be/Ph6ipfZB7z0

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Which Problems Does AI Solve?

There is a dichotomy in artificial intelligence (AI) between the hype surrounding generative AI and the practical realities of its implementation. While AI has the potential to address various challenges across industries, the rush to deploy these technologies has often outpaced their readiness for real-world applications. This has led to a proliferation of AI systems that, while impressive in theory, frequently fall short in practice, resulting in frustration among users and stakeholders.

Generative AI, particularly large language models (LLMs), has captured the imagination of marketers and technologists alike. The excitement surrounding these tools has led to their rapid adoption in various sectors, from customer service to content creation. However, this enthusiasm has not been without consequences. Many organizations have integrated AI into their operations without fully understanding its limitations, leading to a backlash against systems that fail to deliver on their promises. The expectation that AI can solve all problems has proven to be overly optimistic, as many users encounter issues with accuracy, reliability, and relevance in AI-generated outputs.

The initial excitement surrounding AI technologies can be likened to previous hype cycles in the tech industry, where expectations often exceed the capabilities of the technology. The current wave of AI adoption is no different, with many organizations investing heavily in generative AI without a clear understanding of its practical applications. This has resulted in a scenario where AI is seen as a panacea for various business challenges, despite the fact that many tasks may be better suited for human intervention or simpler automation solutions.

One of the critical issues with the current AI landscape is the tendency to automate processes that may not need automation at all. This can lead to a situation where organizations become entrenched in inefficient practices, making it more challenging to identify and eliminate unnecessary tasks. The focus on deploying AI as a solution can obscure the need for organizations to critically assess their processes and determine whether they are truly adding value.

Moreover, the rapid pace of AI development raises concerns about the sustainability of these technologies. As companies race to innovate and bring new AI products to market, there is a risk that many of these solutions will not be adequately supported or maintained over time. This could lead to a situation where organizations are left with outdated or abandoned technologies, further complicating their efforts to leverage AI effectively.

Despite these challenges, there is a consensus that AI has the potential to drive significant advancements in various fields. The ability of AI to analyze vast amounts of data and identify patterns can lead to improved decision-making and efficiency in many areas. However, realizing this potential requires a more nuanced understanding of AI’s capabilities and limitations, as well as a commitment to responsible implementation.

The conversation around AI also highlights the importance of data as a critical component of successful AI applications. While the algorithms and models are essential, the quality and relevance of the data fed into these systems are equally crucial. Organizations must prioritize data governance and management to ensure that their AI initiatives yield meaningful results.

As the AI landscape continues to evolve, it is essential for stakeholders to remain vigilant and critical of the technologies they adopt. The promise of AI is significant, but it is vital to approach its implementation with a clear understanding of its limitations and the potential consequences of over-reliance on automated solutions. By fostering a culture of critical thinking and continuous improvement, organizations can better navigate the complexities of AI and harness its potential to drive meaningful change.

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Podcast Information:

Stephen Foskett is the Organizer of the Tech Field Day Event Series, now part of The Futurum Group. Connect with Stephen on LinkedIn or on X/Twitter.

Alastair Cooke is a CTO Advisor at The Futurum Group. You can connect with Alastair on LinkedIn or on X/Twitter and you can read more of his research notes and insights on The Futurum Group’s website.

Frederic Van Haren is the CTO and Founder at HighFens Inc., Consultancy & ServicesConnect with Frederic on LinkedIn or on X/Twitter and check out the HighFens website

Justin Warren is the Founder and Chief Analyst at PivotNine. You can connect with Justin on X/Twitter or on LinkedIn. Learn more on PivotNine’s website. See Justin’s website to read more.

Thank you for listening to this episode of the Tech Field Day Podcast. If you enjoyed the discussion, please remember to subscribe on YouTube or your favorite podcast application so you don’t miss an episode and do give us a rating and a review. This podcast was brought to you by Tech Field Day, home of IT experts from across the enterprise, now part of The Futurum Group.

#AI #AIFD5 #TFDPodcast #DemitasseNZ #FredericVHaren #GestaltIT #JPWarren #SFoskett #TechFieldDay #TechFieldDayPod

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AI is Not a Fad

The current hype about building massive generative AI models with massive hardware investment is just one aspect of AI. This episode of the Tech Field Day podcast features Frederic Van Haren, Karen Lopez, Marian Newsome, and host Stephen Foskett taking a different perspective on the larger world of AI. Our last episode suggested that AI as it is currently being hyped is a fad, but the bigger world of AI is absolutely real. Large language models are maturing rapidly and even generative AI is getting better by the month, but we are rapidly seeing the reality of the use cases for this technology. All neural networks use patterns in historical data to infer results, so any AI engine could hallucinate. But traditional AI is much less susceptible to errors than the much-hyped generative AI models that are capturing the headlines today. AI is a tool that augments our knowledge and decision making, but it doesn’t replace human intelligence. There is a whole world of AI applications that are productive, responsible, and practical, and these are most certainly not a fad.

https://www.youtube.com/watch?v=BOUTKD8itI4&list=PL4esUX7mpOVYdVlyHmbi5xVGdnRHUa6tH&index=1

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AI Field Day 5 is our next AI event happening September 11 through September 13. Check out the event page on the Tech Field Day website for more details.

Look Beyond the Hype: AI is Real!

The current hype surrounding massive generative AI models and the substantial hardware investments they require is just one facet of the broader AI landscape. While the media often focuses on these large language models and the billions of dollars spent on supercomputers to support them, AI encompasses much more than this. The reality is that AI is not a fad – it is a multifaceted tool that is rapidly evolving and finding practical applications across various industries.

AI can be divided into two main phases: training and inference. The training phase involves using extensive datasets and significant computational power, often requiring numerous GPUs, to build models. This phase is typically handled by a few large organizations with the resources to manage such complexity. On the other hand, the inference phase, where these models are applied in real-world scenarios, is less resource-intensive and more accessible to consumers and enterprises. This division highlights that while the development of AI models may be complex and resource-heavy, their application can be straightforward and widely beneficial.

The demand for AI is driven by consumers and enterprises seeking to simplify and enhance their operations. This demand ensures that AI is not a passing trend but a technology with staying power. However, the term “AI” is often used as a catch-all phrase, leading to confusion about its true capabilities and applications. For instance, generative AI, which includes models like ChatGPT, is just one type of AI. These models can produce impressive and convincing outputs but are also prone to errors and “hallucinations”—generating incorrect or nonsensical information based on the data they were trained on.

Traditional AI, which has been in use for years in various industries, is generally more reliable and less prone to such errors. Applications of traditional AI include anomaly detection in manufacturing, video analysis in retail, and security. These use cases demonstrate AI’s practical and responsible applications, which are far from being a fad. For example, AI is used in agriculture to monitor crop health and improve yields, a task that does not require the massive computational resources associated with generative AI.

The perception of AI as a fad is partly due to the overhyped and sometimes half-baked applications of generative AI that capture public attention. These applications often promise more than they can deliver, leading to skepticism. However, the underlying technology of AI is robust and continues to mature, offering valuable solutions in various fields. The speed of innovation in AI is accelerating, and while this can lead to unrealistic expectations, it also means that practical applications are continually emerging.

AI is a tool that augments human knowledge and decision-making rather than replacing it. This distinction is crucial for understanding AI’s role in our lives. For instance, AI can assist in generating documentation, analyzing code, or improving search capabilities within an organization. These applications enhance productivity and efficiency without replacing the need for human oversight and expertise.

The trust factor in AI is also significant. As AI becomes more integrated into everyday technologies, it is essential to market and implement it responsibly. This includes ensuring that AI systems are transparent, reliable, and used ethically. For example, non-generative AI systems, which do not generate new content but analyze existing data, are generally more trustworthy and less prone to errors.

AI is not a fad; it is a powerful tool with a wide range of applications that are already making a significant impact. While the hype around generative AI may lead to some disillusionment, the broader field of AI continues to offer practical, responsible, and valuable solutions. As AI technology evolves, it will become even more integrated into various aspects of our lives, enhancing our capabilities and helping us solve complex problems. The key is to approach AI with a clear understanding of its strengths and limitations, ensuring that it is used to augment human intelligence and decision-making responsibly.

Podcast Information

Stephen Foskett is the Organizer of the Tech Field Day Event Series, now part of The Futurum Group. Connect with Stephen on LinkedIn or on X/Twitter.

Frederic Van Haren is the CTO and Founder at HighFens Inc., Consultancy & ServicesConnect with Frederic on LinkedIn or on X/Twitter and check out the HighFens website

Karen Lopez is a Senior Project Manager and Architect at InfoAdvisors. You can connect with Karen on X/Twitter or on LinkedIn.

Marian Newsome is the CEO and Founder of Ethical Tech Matters and a cohost of the Tech Aunties Podcast. You can connect with Marian on LinkedIn. Listen to the Tech Aunties Podcast.

Thank you for listening to this episode of the Tech Field Day Podcast. If you enjoyed the discussion, please remember to subscribe on YouTube or your favorite podcast application so you don’t miss an episode and do give us a rating and a review. This podcast was brought to you by Tech Field Day, home of IT experts from across the enterprise, now part of The Futurum Group.

#AI #TFDPodcast #DataChick #FredericVHaren #GestaltIT #SFoskett #TechFieldDay #TechFieldDayPod #TheFuturumGroup

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AI is Not a Fad - The Tech Field Day Podcast

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#SymLink: The QlikConnect event highlighted debates on AI as a science or engineering field, emphasizing user-driven innovation and continuous learning. #Qlik #FredericVHaren #QlikConnect #TFDx #LinkedIn
https://www.linkedin.com/pulse/ai-science-engineering-frederic-van-haren-ihnle
Is AI Science or Engineering?

I attended #QlikConnect with the Tech Field Day team #TFDx this week. I think many delegates have summarized the various sessions well, and there is no need to repeat that.

There is a hazardous amount of AI-generated and SEO-oriented content being generated, and the solution is real stories from real communities. In the first episode of Tech Field Podcast, recorded on-site at AI Field Day, Stephen Foskett chats with Frederic Van Haren, Gina Rosenthal and Colleen Coll about confronting inauthentic content.
#ColleenColl #Digi_Sunshine #FredericVHaren #SFoskett #TechFieldDay #TechFieldDayPod #AIFD4 #TFDPodcast Coverage
https://gestaltit.com/podcast/stephen/content-made-with-ai-is-obscuring-real-information/
Credible Content From the Community is More Important than Ever - Gestalt IT

There is a hazardous amount of AI-generated and SEO-oriented content being generated, and the solution is real stories from real communities. In the first episode of Tech Field Podcast, recorded on-site at AI Field Day, Stephen Foskett chats with Frederic Van Haren, Gina Rosenthal and Colleen Coll about confronting inauthentic content.

Gestalt IT
There is a hazardous amount of AI-generated and SEO-oriented content being generated, and the solution is real stories from real communities #ColleenColl #Digi_Sunshine #FredericVHaren #SFoskett #TechFieldDay #TechFieldDayPod #AIFD4 #TFDPodcast Coverage https://gestaltit.com/podcast/stephen/content-made-with-ai-is-obscuring-real-information/
Credible Content From the Community is More Important than Ever - Gestalt IT

There is a hazardous amount of AI-generated and SEO-oriented content being generated, and the solution is real stories from real communities. In the first episode of Tech Field Podcast, recorded on-site at AI Field Day, Stephen Foskett chats with Frederic Van Haren, Gina Rosenthal and Colleen Coll about confronting inauthentic content.

Gestalt IT
Just Posted: The article "The Bedrock of AI is Data" from Utilizing Tech features a discussion with Qlik's Nick Magnuson and Clive Bearman on how crucial data integration and quality are to the advancement of generative AI and its applications. #Qlik #SFoskett #FredericVHaren #AIFD4 #UtilizingTech #Podcast
https://utilizingtech.com/podcast/season-6/the-bedrock-of-ai-is-data-with-nick-magnuson-and-clive-bearman-of-qlik/
The Bedrock of AI is Data with Nick Magnuson and Clive Bearman of Qlik - Utilizing Tech

Data is the foundation on which AI models are built, and integration of enterprise data will be the key to generative AI applications. This episode of Utilizing Tech brings Nick Magnuson and Clive Bearman from Qlik to discuss the integration of data and AI with Frederic Van Haren and Stephen Foskett. Enterprises sometimes worry that their data will never be ready for AI or that they will feed models with too much low-quality data, and overcoming this issue is one of the first hurdles. Another application for machine learning is improving data quality, organizing and tagging unstructured data for applications. The concept of curated data is an interesting one, since it promises to elevate the value of enterprise data. But what if a flood of data causes the model to make the wrong connections? If data is to be a product it must be profiled, tagged, and organized, and ML can help make this happen. The trend of generative AI is driving budgets and priorities to make data more useful and organized, but even unstructured data streams can be valuable. The application of large language models to structured data is promising as well, since it enables people to query these data sets even if they lack the background and skills to construct queries.

Utilizing Tech
The Utilizing Tech podcast returns for another season focused on AI. Frederic Van Haren is co-hosting this season with Stephen Foskett, and discussions will delve into how enterprises integrate AI across various sectors, focusing on their infrastructural stack and data pipeline management. As AI cements its omnipresence in technology, this season promises to unpack its applications and influence in current and future markets.
#FredericVHaren #UtilizingTech #AIFD4 #Podcast
https://highfens.com/2024/02/12/podcast-season-6-season-opener/
Podcast - Season 6 - Season opener - HighFens Inc.

The Utilizing AI podcast is back after a break of fewer than two years under the Utilizing Tech umbrella! A lot has changed since then. Generative AI has made a

HighFens Inc.
The Utilizing Tech podcast returns for another season focused on AI #FredericVHaren #UtilizingTech #AIFD4 #Podcast https://highfens.com/2024/02/12/podcast-season-6-season-opener/
Podcast - Season 6 - Season opener - HighFens Inc.

The Utilizing AI podcast is back after a break of fewer than two years under the Utilizing Tech umbrella! A lot has changed since then. Generative AI has made a

HighFens Inc.
#SymLink: The article announces the return of the Utilizing AI podcast for its sixth season on highfens.com, discussing the evolution of AI, the impact of generative AI, and engaging with enterprise AI use cases. #FredericVHaren #AIFD4 #UtilizingTech #Podcast
https://highfens.com/2024/02/12/podcast-season-6-season-opener/
Podcast - Season 6 - Season opener - HighFens Inc.

The Utilizing AI podcast is back after a break of fewer than two years under the Utilizing Tech umbrella! A lot has changed since then. Generative AI has made a

HighFens Inc.