"Flipping the classroom" is an educational approach where students first encounter new material outside of class, typically through video lectures or reading assignments, and then use class time to work on problem-solving, discussions, or other active learning strategies. Generative AI can play a significant role in facilitating and enhancing this approach in various ways:

Transcript for Disambiguation Podcast Episode 2 with Guest Jakub Stefaniak

AI technology has revolutionized the way we approach data analysis and modeling. For these applications to be successful, though, the data must be properly prepped. Data preparation is the process of organizing data into a format that can be used to create effective AI models. Without proper data preparation, AI models will not be able to effectively analyze and interpret data. As technology advances, artificial intelligence (AI) models and algorithms are becoming increasingly important for businesses and organizations around the world. However, the success of these AI models and algorithms is dependent on how well the data is prepared. Data preparation is essential for ensuring that AI models and algorithms are accurate, reliable, and effective.

Disambiguation, a podcast that aims to "remove the confusion around" artificial intelligence (AI), generative AI and business automation by looking at the business solutions available today to improve business outcomes and gain competitive advantage. Check it out on YouTube or any of the major podcast platforms.

Generative AI has revolutionized the way we think about Artificial Intelligence (AI) and its applications. By incorporating generative AI into a cloud-based platform, you can unlock an unprecedented level of efficiency and innovation for your applications. With generative AI, you can leverage advanced AI technologies to create intelligent solutions tailored to your specific needs. In this post we’ll explore how generative AI can enhance the services of a cloud-based platform and increase the effectiveness of applications built on the cloud platform.

We are excited to announce the official launch of the Disambiguation podcast.

"Disambiguation is the process of removing confusion around terms that express more than one meaning and can lead to different interpretations of the same string of text."

Host Michael Fauscette of Arion Research; a leading technology analyst, tech startup advisor, consultant, board member, and storyteller; and his guests "remove the confusion around" artificial intelligence (AI), generative AI and business automation by looking at the business solutions available today to improve business outcomes and gain competitive advantage.

Infographic from the AI Adoption survey, August 2023.

Since last fall there has been a rapidly growing obsession with generative AI and particularly OpenAI’s ChatGPT. There are a number of open and closed large language models (LLM) from a variety of startups gaining users at a whirlwind pace, as well as several cloud providers offering open integrations and LLMs of their own. The buzz on generative AI started mostly positive but as with most technology there quickly emerges a darker side as well. For generative AI this ranges from the capability to generate overwhelming misinformation campaigns to security and privacy challenges.

In a recent announcement, Salesforce unveiled its new all-in-one CRM solution, “Starter”, designed with the needs of small and growing businesses in mind. Starter combines the functionalities of sales, service, and marketing in a single solution and is the next iteration of Salesforce Easy, which was launched last year as Salesforce’s first product led growth (PLG) offering. By bringing these capabilities together in a simpler package, Salesforce believes that it can provide important capabilities to these businesses for managing customer relationships, centralizing critical data, and fostering efficient growth. The solution provides an easy-to-use user interface (UI) featuring guided onboarding, reporting templates, unified customer data, built-in AI, and pre-built dashboards.

Here’s an announcement from the US Securities and Exchange Commission (SEC) that may have slipped by you this week. The SEC adopted new rules requiring public companies to disclose material cybersecurity incidents and provide annual information on their cybersecurity risk management, strategy, and governance; and includes foreign private issuers as well. The goal is to provide investors with consistent, comparable, and useful cybersecurity information in a timely manner.

The digital landscape has rapidly evolved over the years, with technology like Artificial Intelligence (AI) finding itself at the forefront of innovation. However, these advancements aren't solely beneficial. The dark underbelly of this progress is that malicious entities are leveraging these tools to conduct highly sophisticated cyberattacks. The increasing risk of security hacks, data breaches, and other forms of cybercrime is an escalating concern for businesses and organizations worldwide. By harnessing the power of AI, hackers can automate their attacks, resulting in more frequent, rapid, and complex cyber threats. It's not just the scale but also the severity of these attacks that have increased, with high-value targets like financial institutions and government agencies bearing the brunt.

Meta announced a new version of Llama (Large Language Model Meta AI), Llama 2, and made it open source. Meta believes an open source approach fosters collaboration, iteration and transparency, which is important for new technologies like large language models. Providing access to tools and computing power can create opportunities for businesses, startups, and researchers. Llama 2 was trained on 40% more data than the original Llama model. In addition the announcement included two important partnerships with Microsoft and Qualcomm.

When it comes to interacting with your customers’ for sales, marketing and customer service consumers are clear, they want what they want, when and how they choose. That’s not a new concept, but is a map to improved customer experiences. Offering the channel that a prospect or customers trusts and prefers is much more likely to lead to a positive outcome for the interaction.

Yesterday Salesforce announced a broad price increase for Sales Cloud, Service Cloud, Marketing Cloud, Industries and Tableau of on average 9%, starting Aug 1st, 2023. This is the first broad price increase since 2016, although a lot has changed over that 7 years; particularly in the addition of several high profile acquisitions to the product portfolio, and in product packaging, which has changed fairly often over that time period.

Customer journey mapping is dead. Okay, a little blunt, I suppose I should say it as “the exercise of building static journeys for prospects and customers is no longer the best approach to understand and interact with customers”. All the research I’ve done on buyer behavior shines a light on how ineffective the process and concept is today. Maybe it never was the most useful exercise, but at least in a pre-smartphone world it was reasonable to assume that your company was an important source of information on your products and services, and how a purchaser could use them to their benefit. Once the prospects had access to the entirety of the Internet’s information in their pockets, the buying process changed. Gone is the need for the vendor to be the only source of information on their products and services. Buyers can research, read reviews online for almost anything they want to purchase; connect with others that have experience with the potential solutions, in their industry, and with similar challenges; and generally eliminate the need to interact with a vendor until the decision to purchase is nearly decided, or is already made.

If you told me 20 years ago that I’d be writing an article that had the phrase “artificial empathy” in the title I’d probably have hurt myself laughing…yet here we are. The use of chatbots, particularly in customer service and support (call center) activities continues to increase rapidly. Customer expectations for “good” digital experiences are high, and the past 3+ years has seen record numbers of people online and using digital channels. In addition to the consumer behavioral changes businesses have faced several challenges including difficulty hiring and retaining qualified employees, friction with employees over working from home or returning to the office, and very difficult economic pressures, all of which created a resource constrained work environment. This is a considerable challenge for many businesses that has resulted in wider deployment of automation, specifically chatbots to reduce the burden on employees.

Today IBM announced the intent to purchase Apptio, a cloud-based financial and operational IT management and optimization solution (FinOps) for $4.6 billion from Vista Equity Partners. Vista paid $1.94B to take Apptio private in 2018. This move signifies IBM’s strategic push to bolster its cloud and enterprise offerings, as it integrates Apptio's unique expertise and portfolio into its ecosystem.

As technology evolves at an exponential pace, businesses must adapt to stay competitive. One of the most exciting developments in recent years is Generative AI, which can generate new data that is similar to the data it has been trained on. There is a lot of “hype” around AI and generative AI recently but let’s look beyond the hype at how Generative AI can be a competitive advantage for sales and marketing teams looking to enhance their strategies and drive more revenue.

Everywhere you look (or listen) lately you will see some new article on AI, large language models like ChatGTP, robotics and automation in general. Don’t misunderstand me though, it is exciting and there are lot’s of new use cases that offer some real world business value. AI isn’t new of course, its history goes back decades to the early 1950’s. What has changed the evolution of the technology though is a combination of the Internet’s impact on the creation, collection and distribution of data and a massively scaleable compute infrastructure. The other shift that fuels this “hype” is the openness of businesses and institutions to choose to invest in automation and AI. There are a number of reasons for that, including the business disruption and changes caused by the COVID-19 pandemic and its aftermath including labor shortages, broad shifts to remote work, the subsequent noise of “return to office”, inflation and the rapid increase of interest rates, threats of a recession, and the threat of the US debt default (mischief managed, at least for now). In other words, businesses are feeling pressured from many fronts to change and adapt in order to stay competitive and healthy.

Earlier this year I co-hosted an episode of In the Hot Seat looking at Generative AI in higher education. I was lucky to be joined by Dr. Ali Green from the University of West Florida and Keeley Meentze from The Keeley Company, along with my co-host Professor Stephen LeMay, also from the University of West Florida. Artificial intelligence (AI), particularly generative AI using large language models (LLMs) like ChatGPT, has sent shockwaves through various sectors including higher education. Along with a great deal of controversy, the discussion of generative AI in education, at least among a subset of educators, has shown a strong potential as a pivotal tool in reshaping and improving higher education. Built upon frameworks such as GPT-4 from OpenAI, generative AI can analyze vast amounts of data, learn patterns, and generate new content autonomously. This capability has far-reaching implications for higher education, offering transformative possibilities that promise to revolutionize teaching, learning, and administrative tasks.