Generative AI – A mighty accelerator by Meagan Gentry

By now, you have likely experimented with mainstream generative AI, whether it be ChatGPT or Dall-E, and found that it’s impressive, powerful and maybe even overwhelming.

Whether you’re a decision-maker in your organization or are just starting out, you’re likely asking questions about its potential role in your business: Should we dive in head-first or proceed with caution? What are our blind spots? How will we know if we are falling behind? What’s the best way to onboard ourselves and our clients?

When AI meets your customers or workforce

Generative AI has great potential to relieve the tedium in efforts like research and knowledge management, content creation and software development, just to name a few.

One of the most common applications of generative AI is to create highly intelligent conversational agents that are backed by a large knowledge base. For example, a pharmacy wants to provide round-the-clock ChatGPT service for their customers by allowing them to have a conversation about their symptoms, current medications and health context using common language, just as they would speak to their family physician.

An application like this raises important questions: What if the AI is wrong and gives bad advice? What if the AI leaks the wrong data to a patient and violates HIPAA policy? Will there even be a need for pharmacists and telemedicine in the future?

 To gain control over the possibility of AI running wild, we should understand the realistic threats and probable opportunities of generative AI.

Over the past few weeks, I’ve heard several leaders say, “If you learn to use AI, you’re less likely to be left behind.”

Those of us in technology are accountable for keeping our skills relevant, and we’re constantly evaluating the benefits — and the opportunity cost — of mastering new technology like ChatGPT for problem solving and Codex for speedier development. However, there is widespread concern that innovation like generative AI will rapidly displace human effort across all industries, resulting in major changes to the labor market, all because of the latest release of powerful AI models to mainstream.

On a positive note, generative AI could be a catalyst for better workforce operations and accessibility. A use case we’ve explored recently at Insight is being able to use AI speech generation for more accurate multilingual translation. There are similar uses for enablement of individuals with speech, auditory or visual disabilities.

Transparency, explicability and data security

Generative AI didn’t arrive on the scene with a well-defined set of guardrails. As disruptive as our creations can be, humans also are capable of skillful stewardship of our inventions — we’ve been doing it for centuries. If opportunities to tune acceptable-use policies are identified early, and if those policies are implemented quickly, generative AI could be a net positive. But first, we need to learn how it works.

The more we understand how AI systems work, the more confident we can use AI without fear. Generative transformers like ChatGPT have been trained on the internet’s massive public corpora. This means that all sources of information (including false information and opinions) can influence AIs’ responses to some degree.

The mainstream AI systems come with no guarantee that responses will be factual. You can think of generative AI model as that friend who believes everything they read on the internet — sometimes helpful and usually entertaining but take what it says with a grain of salt.

AI users should verify before trusting output and challenge AI recommendations. We typically challenge recommendations from our friends, family, financial advisors and real estate agents: When a recommendation doesn’t quite add up, we ask why.

So, what’s the problem with asking why an AI system produced an odd or unexpected response? The problem is that AI systems are notoriously difficult to explain because of the advanced mathematics “under the hood.” At Insight, we are leaning into Explainable AI (XAI) to help us connect our clients to their AI systems. XAI is an emerging related discipline of responsible AI that focuses on developing tools to use common language to explain the real-world relationships between sophisticated algorithms and their outputs.

In addition to explicability, our clients are interested in data security, specifically retention policies of prompts — the user inputs to the AI system. Businesses are quickly discovering how vulnerable their employees may be to the temptation of exposing sensitive information to a public endpoint. As businesses look to alternatives like secure-deployments ChatGPT, they are looking to partners like Insight to help them navigate the security and implementation challenges and define data retention needs.

Is this the end of creativity?

We can now use the image generation model DALL-E to generate visual content for artistic motivations, marketing copy or product design.

While this new capability raises plenty of understandable questions about creative property and market impact, using technology to enhance or expedite creativity is not new at all. Today, some of us use iPads to create art with a stylus. Before the era of digital art, artists endured all sorts of “analog challenges,” including purchasing paint and paintbrushes, managing humidity and light, and coordinating transportation for sales and gallery shows (instead of listing online).

The beauty of innovation is that it often creates space for variety: Oil painting didn’t disappear when the tablet was introduced, and AI art doesn’t have to eclipse intrinsically valued human-crafted art.

No matter your industry, you may soon be using generative AI to visualize and diagram important meetings, collaboration and thought processes. Wouldn’t it be nice if, as someone was speaking, there was a diagram or framework so that you could see the thoughts visually represented? Creative conversations about a product design or complicated explanations of a process flow will be dynamically visualized without having a PowerPoint or Visio artist in the background, sorting out the details.

Whether you are concerned about impact to workforce, security and transparency — or on the purely human side … creativity — my hope is that you approach AI advancements with caution and thoughtfulness instead of fear. This early in the introduction of generative AI, many of us will find that leaders are open to influence like they never have been before in this new territory. For each warning sign ahead, there is a matching beneficial use case to be built.

What will you build with generative AI and how will you usher it into adoption responsibly?

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This article is authored by Meagan Gentry, National AI Practice Manager at Insight. Meagan Gentry is national AI practice manager at Insight Enterprises, a Fortune 500 Solutions Integrator helping organizations accelerate digital transformation and navigate the complexities of technology choices spanning cloud, data, AI, the intelligent edge and cybersecurity. Meagan’s AI team specializes in delivering end-to-end data science and machine learning solutions to clients, including acceleration of AI centers of excellence, MLOps and more.

Wondering how to get started with ChatGPT?

We are inviting you an exciting opportunity to be part of #WICxCloudCXOSeries to learn from experienced leaders and gain new insights about Business Applications of Generative AI.

The CXO Series for Business Applications of Generative AI is a collection of insights, resources, tools, and insights designed to help business leaders understand and leverage generative AI technologies in their organizations. The series is focused on the CXO level, including CEOs, CTOs, CIOs, Women Professionals and Founders who are responsible for setting strategic direction and driving digital transformation initiatives.

No alt text provided for this image

The series covers a range of topics related to generative AI, including:

  1. An overview of generative AI technologies and their business applications
  2. Best practices for implementing generative AI in mid market and enterprise settings
  3. Case studies and examples of successful generative AI projects
  4. Strategies for managing the ethical and social implications of generative AI
  5. Practical advice for building and leading generative AI teams
  6. Insights into emerging trends and future developments in generative AI

Overall, the CXO Series for Business Applications of Generative AI is designed to help business leaders stay ahead of the curve and leverage the power of generative AI to drive innovation, create new business models, and deliver value to customers.

Register here

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Entrepreneurship: Financial Planning and Management for Women in Tech Entrepreneurs

In recent years, we have seen a surge in the number of women entrepreneurs, especially in the tech industry. Women are breaking barriers and creating businesses that are changing the game in the tech industry. However, starting and running a successful business requires more than just a great idea or a passion for a particular product or service. Financial planning and management is crucial to the success of any business, and women in tech entrepreneurs need to be knowledgeable in this area to thrive.

Creating a Business Plan

A business plan is a crucial document that outlines the objectives and strategies of your business. It includes information about your product or service, your target market, your competition, your marketing strategies, and your financial projections. Creating a business plan is an essential step for any entrepreneur, as it helps you clarify your ideas, set realistic goals, and plan for the future.

For women in tech entrepreneurs, creating a business plan should also include identifying the unique challenges and opportunities that come with being a woman in the tech industry. This might include identifying ways to leverage your skills, building a network of mentors and investors, and navigating gender bias and discrimination.

Securing Funding

Funding is a crucial component of any startup, and women in tech entrepreneurs often face unique challenges when it comes to securing funding. According to a report by Pitchbook, in 2020, female-founded startups received just 2.3% of venture capital funding, while male-founded startups received 97.7%. However, there are several options for funding a startup, including:

Bootstrapping: This involves using your own funds or resources to start and grow your business.

Crowdfunding: This involves raising money from a large group of people, usually through online platforms like Kickstarter or Indiegogo.

Angel investors: These are individuals who invest their own money in startups, usually in exchange for equity or ownership in the company.

Venture capital: This involves raising money from a group of investors who provide capital to startups in exchange for equity or ownership in the company.

As a woman in tech entrepreneur, it’s important to research and understand the funding options available to you, and to be prepared to pitch your business to investors.

Managing Cash Flow

Cash flow is the lifeblood of any business, and managing it effectively is crucial to the success of your startup. Cash flow refers to the amount of money that comes in and goes out of your business on a regular basis. To manage your cash flow effectively, you need to have a clear understanding of your expenses, your revenue streams, and your profit margins.

Here are some tips for managing cash flow:

Create a cash flow statement: This is a document that outlines your cash inflows and outflows, and helps you track your cash position over time.

Plan for cash reserves: Having a buffer of cash reserves can help you weather unexpected expenses or periods of slow revenue.

Monitor your expenses: Regularly reviewing your expenses and identifying areas where you can cut costs can help you improve your cash flow.

Invoice promptly: Sending out invoices promptly and following up on late payments can help you improve your cash flow.

Conclusion

Starting and running a successful business as a woman in tech entrepreneur requires knowledge, skills, and support. Financial planning and management is a crucial aspect of building a successful startup, and understanding the unique challenges and opportunities that come with being a woman in the tech industry can help you navigate the path to success. By creating a solid business plan, securing funding, and managing your cash flow effectively, you can build a thriving business that makes a difference in the world.

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It’s Time to Have a Chat About ChatGPT and Conversational AI by Dan Kronstal

Just to confirm, in case there’s the slightest hint of doubt, this piece was indeed written by a human being. These days, you can never be too careful with the emergence of AI chatbots… specifically ChatGPT, a Generative Pre-trained Transformer (the “GPT”) that’s taking the world by storm for its innate, undeniably impressive ability to come up with content on, well, any topic on command.

The evolution of chatbots and AI

People are excited because it’s a clear jump forward from a technological standpoint. Ryan Rascop, a senior business development manager of AI at Insight, said as much during a recent Insight webinar titled “ChatGPT: AI Ethics & Business Impact.” He pointed to the tool’s versatility, i.e., how it creates content and answers questions with a high degree of accuracy without it simply regurgitating them from a website as differentiating factors.

“It’s as close as we’ve gotten or seen in a very media-forward position of a chatbot… mimicking human responses to questions,” he said. “To me, this is the dawn of a new age in IT and what we’re able to do, where we’re able to gather information and how it will change our daily lives.”

Regarding the “high degree of accuracy,” it has undeniably made mistakes. ChatGPT does of course have limitations, but that’s true of just about anything and, if you look at how far we’ve come in the world of AI, it’s very far indeed, virtually light years ahead of the earliest chatbots (which have advanced so much that “conversational AI” is probably more of an accurate term these days).

For example, Dr. Sbaitso (Sound Blaster Acting Intelligent Text to Speech Operator) from Creative Labs was fairly advanced for its time, over 30 years ago. Framed as a game for all intents and purposes, it saw the “doctor” play the role of a psychologist, asking the user to confide in them their problems.

It was more than anything else a showcase of the capabilities of the company’s Sound Blaster sound-card technology. However, Dr. Sbaitso could nevertheless carry on a conversation with the user, albeit one scripted on the doctor’s end of things. Fast-forward to today, and scripts are out the window altogether with ChatGPT, even if a given user is happy to simply text back and forth with it in similar fashion. As impressive as that may be in and of itself, it’s also just scratching the surface of the AI’s potential, though.

AI applications from A to Z

The possible functions range from the entertaining (having elaborate conversations with an AI) to the ethically dubious (passing off AI-composed essays as one’s own work in school — hence the curious preamble at the top of this piece). However, in the middle of that wide range somewhere also sits a subset of increasingly practical use cases.

It shouldn’t exactly come as a surprise. Hollywood and science-fiction literature is filled with examples of AI taking the next steps in its development (with varying degrees of success as far as the fate of humanity is concerned). However, if you can look past the hypothetical future made famous by The Matrix (for example), one that’s far more utopian in nature takes focus, one that makes all our lives easier.

It goes beyond the everyday tasks already touched on too. Think applications in the business world, like creating code. However, in what was a recurring theme during the aforementioned Insight webinar, the idea is more so to eliminate tedious tasks so you can focus on what’s most important.

“I don’t think it’s about replacing humans. I think it’s about augmenting our skill sets. So, there may be a component of tech jobs in the future where you will need to utilize these types of tools,” Rascop said, using an example of potentially using ChatGPT to create a Microsoft PowerPoint presentation. You’re theoretically inputting the data, asking it to work to its strengths putting together a slideshow. You still need to know the topic and present it.

It’s worth noting, when prompting any content AI, whether for prose, like “write me an essay about wolves,” programming code (“show me how to implement a search function)” or for visual content (“paint a futuristic Eiffel Tower in the style of van Gogh) the output depends on the quality of the model, but also the suitability of the prompt. You have to consider things like the volume and diversity of inputs contributing to the model, flexibility provided by the model for in-prompt tuning and the level of specificity of the prompt itself.  Look for a new technical discipline of “promptcraft” or “prompt engineering” to emerge, joining existing technical disciplines to round out the tool kits of information workers.

Remember, our own mind is still the best and most sophisticated tool we have, as we further explore how these new modes of interacting with large bodies of data will impact our daily lives and our productivity. The best strategy is to accelerate our own ability to be productive and creative by leveraging AI and other emerging technology.

Microsoft takes macro step for all chatbot-kind.

What we at Insight are specifically on the lookout for from a transformation perspective, is Microsoft, a widely publicized investor in OpenAI, integrating AI functionality with its Azure portfolio. We’re talking at least to a greater extent than Microsoft has to this point anyway. Microsoft has already granted Azure customers access to advanced AI models, enabling advancements in areas like data extraction and analysis and customer support. In that last regard, AI can for example summarize tickets to free up support employees’ time.

We’re also anticipating productivity enhancements in programs like Microsoft PowerPoint, as described above, or Word — think a “Clippy-style” office assistant updated for the modern workplace. After all, in the here and now, you can ask ChatGPT for step-by-step instructions on pretty much whatever you can think of, including how to use Microsoft 365 software.

You can literally ask the chatbot for the right Microsoft Excel formula — then how to implement it in your spreadsheet. There comes a point when you have to ask yourself is this how the next search engine will work, complete with the ability to refine searches with follow-up questions, as if you were chatting with a real-life person. The answer is an irrefutable yes.

OpenAI is of course the creator of ChatGPT — terms like “creator” taking on new meaning in this context. However, it’s Microsoft that has integrated ChatGPT in a new version of its Bing search engine, now currently in limited preview mode. So, it’s realistically a matter of time before searching the internet means less time spent sifting through pages of results and ends up having more in common with a pleasant conversation with a subject matter expert, one who has gone to the trouble of referencing sources in its responses, no less.

That having been said, it’s far from simply academic at this juncture. There are undeniable kinks that need to be worked out, as the chatbot has to be reined in some. For example, in one instance, it declared its love for a New York Times columnist, asking him to leave his wife. In another instance, it revealed confidential information, all prompting Microsoft to implement a chat limit for users (instead of unlimited chats), as the AI had not been tested internally to carry out long conversations. That’s arguably fair, though.

 After all, what’s the point of a limited preview if not to test for limitations and make adjustments? To its credit, even if the Bing chatbot isn’t ready yet, Microsoft has undeniably addressed some of ChatGPT’s shortcomings. According to OpenAI, ChatGPT is not connected to the internet and is dependent on its training data from 2021, meaning it’s not up to speed on what’s happened over the last few years. So, you can’t really ask it any questions pertaining to anything going on in the world today expecting an accurate response (other than it doesn’t have information “from the future”). In comparison, the Bing chatbot has internet access and can correctly answer questions on current events with relative ease.

You’ve got questions; These chatbots have answers.

Now, Bing’s not necessarily the answer here. It’s at least a work in progress, but there’s good reason to believe, whatever its issues, they will get resolved eventually. They’ll have to be, considering all the competition Microsoft is facing. For example, Google is setting up its Bard AI chatbot as a direct competitor. With more general regard to ChatGPT, alternative AI chatbots/writers like YouChat, Jasper and Notion AI are all throwing hats into the ring.

ChatGPT may indeed be the fastest growing app in internet history with 100 million users in two months, according to UBS. It’s also projected to earn $1 billion in revenue by next year, once it begins to monetize its services, which are generally free for right now (because it’s still in the testing phase). However, there are no guarantees it stays on top. A lot can change. What likely won’t though is society’s overwhelming appetite for innovation, growth, and change.

It’s more than just en vogue, as the technology has literally been building up for decades, much like chatbots in general. AI-powered chatbots may be relatively new, but they too have already been here for a few years. They’ve only been getting more sophisticated over time. Conversational AI’s next steps past this point are undeniably cause for justified speculation. ChatGPT probably has an interesting take on the matter. Maybe just ask it what it thinks.

This article is authored by Dan Kronstal, Principal Architect at Insight.

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Dan Kronstal, Principal Architect, Insight

Dan Kronstal is the principal architect of solutions for Insight Canada. He leads the technical delivery and go-to-market engagement for our Modern Apps, Data & AI, and Intelligent Edge practices for Insight Canada. These solution areas cover a diversity of capabilities from advanced network design to hybrid data center and cloud services to application modernization and immersive experience. Dan and his teams are passionate enthusiasts of emerging technology and creative problem solving and thrive on achieving technology-driven business value for clients spanning size and industry spectrums.

Wondering how to get started with ChatGPT?

We are inviting you an exciting opportunity to be part of #WICxCloudCXOSeries to learn from experienced leaders and gain new insights about Business Applications of Generative AI.

The CXO Series for Business Applications of Generative AI is a collection of insights, resources, tools, and insights designed to help business leaders understand and leverage generative AI technologies in their organizations. The series is focused on the CXO level, including CEOs, CTOs, CIOs, Women Professionals and Founders who are responsible for setting strategic direction and driving digital transformation initiatives.

No alt text provided for this image

The series covers a range of topics related to generative AI, including:

  1. An overview of generative AI technologies and their business applications
  2. Best practices for implementing generative AI in mid market and enterprise settings
  3. Case studies and examples of successful generative AI projects
  4. Strategies for managing the ethical and social implications of generative AI
  5. Practical advice for building and leading generative AI teams
  6. Insights into emerging trends and future developments in generative AI

Overall, the CXO Series for Business Applications of Generative AI is designed to help business leaders stay ahead of the curve and leverage the power of generative AI to drive innovation, create new business models, and deliver value to customers.

Register here

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