Our AI writing assistant, WriteUp, can assist you in easily writing any text. Click here to experience its capabilities.

AI for execs: How to cut through the noise and deliver results

View Original View Raw

Summary

AI has had a major impact on the tech and business worlds, with millions of AI-based app downloads and billions in funding for AI startups. Businesses have an opportunity to adopt AI-driven solutions, but decision-makers must choose which solutions are most likely to give them the best ROI with minimal risk. Enterprises should think of AI as a toolkit, consider the maturity and development level of each solution, start with the problem, use AI in a contained setting to get team and management buy-in, have the correct data infrastructure and policies, have human oversight, and consider existing pain points that do not require the generative component of AI.

Q&As

What new applications have AI enabled that have been downloaded millions of times by Android users?
ChatGPT and DALL·E are new applications that have been enabled by AI and have been downloaded millions of times by Android users.

What is the recommended approach when considering the best opportunities for LLMs to make a serious impact on businesses?
The recommended approach when considering the best opportunities for LLMs to make a serious impact on businesses is to start with the problem rather than the exciting new AI solution, think of AI capabilities as a toolkit to accelerate their vision, and consider the differing maturity and development levels of each solution.

What is the "human on the loop" model in regards to AI systems?
The "human on the loop" model in regards to AI systems is a model where systems do not rely on human input to perform their activity (as traditional “human in the loop” systems did) but instead push human control farther from the center of the automated decision-making, playing a review role in ensuring the output is accurate and reliable.

What is the most talked-about new use case for generative AI?
The most talked-about new use case for generative AI is within marketing, particularly copy and imagery generation.

What should businesses consider when identifying the best AI solution for their business?
When identifying the best AI solution for their business, businesses should consider their key business pain points and inefficiencies, the differing maturity and development levels of each solution, their existing business processes and infrastructure, and the need for human oversight.

AI Comments

👍 This article provides a great summary of the power of generative AI and its potential applications in various businesses. It is also full of useful advice on how to approach AI solutions and how to maximize ROI.

👎 The article fails to mention any potential drawbacks of AI solutions, which can be costly and disruptive. It also fails to address potential ethical and security concerns that arise from using AI.

AI Discussion

Me: It's about how AI has been dominating the global tech scene and how decision-makers and investors can cut through the noise and deliver results. It goes into detail about different AI applications, the risks associated with them, and how to identify the best AI solutions for businesses.

Friend: That's really interesting. What implications does the article have?

Me: Well, the article highlights the importance of staying up to date with the latest AI innovations and technologies, and also emphasizes the need for businesses to properly evaluate and assess AI solutions to ensure they get the best return on investment with minimum risk. It also suggests starting small with AI, doing research to identify which solutions are best suited to address particular business pain points, and having human oversight over data and AI to ensure accuracy.

Action items

Register for VB Transform 2023 On-Demand to access the library of featured sessions.
Identify key business pain points and inefficiencies to determine which AI solutions are best suited to address them.
Invest in data management infrastructure and data education to ensure AI systems are used effectively and with human oversight.

Technical terms

AI: Artificial Intelligence. A branch of computer science that focuses on creating intelligent machines that can think and act like humans.
LLMs: Large Language Models. A type of artificial intelligence (AI) that uses natural language processing (NLP) to generate text or speech.
ChatGPT: A large language model (LLM) developed by OpenAI that can generate text based on a given prompt.
DALL·E: A large language model (LLM) developed by OpenAI that can generate images based on a given prompt.
Metaverse: A virtual world or universe, typically one that is populated by users in a shared online environment.
Blockchain: A distributed digital ledger that records transactions across multiple computers in a secure and immutable way.
Fintech: A portmanteau of “financial technology”, referring to the use of technology to provide financial services.
Insurtech: A portmanteau of “insurance technology”, referring to the use of technology to provide insurance services.
ROI: Return on Investment. A measure of the profitability of an investment, calculated by dividing the gain from the investment by the cost of the investment.
Gen AI: Generative Artificial Intelligence. A type of artificial intelligence (AI) that can generate new data, such as text or images, based on a given prompt.
Hallucination: A false perception or belief that is not based in reality.
Unstructured Data: Data that does not have a predefined structure or format.