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Tuesday, August 29, 2023

ChatGPT Enterprise : New Possibilities, New Challenges

OpenAI just launched ChatGPT Enterprise. This is a significant milestone in the intersection of AI and the corporate world. Marketed as an enterprise-grade solution with advanced security, data protection, and unlimited access to GPT-4 functionalities, it is projected to fundamentally reshape work processes within organisations.The launch of ChatGPT Enterprise is likely to have a significant impact on enterprises in a number of ways. By automating tasks, reducing costs, improving customer service, and driving innovation, ChatGPT Enterprise can help enterprises to achieve their goals and become more competitive. Here are some of the potential impacts:

A. Improved productivity: ChatGPT Enterprise can be used to automate a variety of tasks, freeing up employees to focus on more strategic work. For example, ChatGPT can be used to generate reports, answer customer questions, or even write code.

B.Enhanced innovation: ChatGPT Enterprise can be used to help enterprises innovate by providing new ways to generate ideas, solve problems, and create new products and services. For example, ChatGPT can be used to generate new product concepts, write marketing copy, or even design new user interfaces.

c. Reduced costs: ChatGPT Enterprise can help to reduce costs by automating tasks that are currently performed by humans. For example, ChatGPT can be used to answer customer support tickets, which can free up human agents to handle more complex issues.

D. Improved customer service: ChatGPT Enterprise can be used to provide better customer service by providing 24/7 support that is always accurate and up-to-date. For example, ChatGPT can be used to answer customer questions, resolve issues, or even provide product recommendations.

E. Improved decision-making: ChatGPT Enterprise can be used to help enterprises make better decisions by providing access to insights and data that would not be otherwise available. For example, ChatGPT can be used to analyze customer data, identify trends, and make predictions.

Here are some specific examples of how ChatGPT Enterprise could be used in enterprises:

- A customer service team could use ChatGPT Enterprise to answer customer questions, resolve issues, and provide support 24/7.

- A marketing team could use ChatGPT Enterprise to generate new product concepts, write marketing copy, and create social media posts.

- A sales team could use ChatGPT Enterprise to qualify leads, generate proposals, and close deals.

- A product development team could use ChatGPT Enterprise to brainstorm new ideas, research competitors, and test new features.

- A finance team could use ChatGPT Enterprise to analyze financial data, identify trends, and make predictions. As the technology continues to develop, we can expect to see even more innovative and creative uses for ChatGPT Enterprise in the future.

Now, the caveat : However, this technological leap raises a set of key legal issues in the realms of data protection, intellectual property (IP), and the forthcoming AI Act’s foundation model regulatory obligations. ChatGPT Enterprise assures users of robust data protection, stipulating that the model is not trained on business-specific data and that all conversations are encrypted both in transit and at rest. OpenAI claims the platform's SOC 2 compliance adds an additional layer of trust in its security protocols. The rules will have t chan ge in respect of customers/enterprises further finr tuning the model - and reexamining the impact on data, security, ownership, copyright etc. Similarly creative work, technical block of worl created by GenAI both by the enterpiseand by third parties employed by them opens the issue of ownership, copyright etc, Also, monopoly laws may begging to kick in upon mass adoption. The US District Court last week ruled that AI generated work cannot be copyrighted. There are complex legal and regulatory challenges that are expected to be raised and addressed. Overall, the launch of ChatGPT Enterprise is a significant development that has the potential to revolutionize the way enterprises operate.

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Sunday, August 27, 2023

Generative AI: It’s Game Even

While there are very incisive views on Generative AI and a magnitiude of perspectives on opportunities across sectors, spaces and geograohies foreseen, there is this thought provoking article “undisrupted” in the current issue of Economist(very telling it does not state who the author is),- in a nutshell arguing, “that despite the transformative potential of generative AI tools such as ChatGPT, large established companies are unlikely to be overthrown by AI-driven startups.The article posits that incumbents like Microsoft and Salesforce have advantages in distribution and others have valuable proprietary datasets, such as McKinsey and Bloomberg’ with its financial data. It argues that these resources allow them to integrate AI into existing products, thereby fortifying their market positions.

The article also highlights that the existing infrastructure enables easy adoption of AI models from giants like OpenAI and Alphabet Inc. limiting opportunities for new entrants.Lastly, historical data is cited; only 52 of the Fortune 500 companies were established after 1990, implying that disruption has not accelerated significantly over the years.”

On a related note, It's an impressive thought, that Nvidia's Jensen Huang's view in their earning call on VmWare, where in distributing the Genai kit through them, the focus is on supporting the management system, the operating system, the security and software-defined data center approach of enterprises and moves like this catapult both the big and the upstart to delve into GenAI on an entirely new baseline of readiness and maturity. Very interesting, though i feel that the author underestimates the potential for disruption from these startups. First , the article assumes that incumbents can easily integrate AI into their existing products. This is not always the case. AI can be complex and difficult to implement, especially in large, legacy systems. Startups, on the other hand, are often more nimble and can move more quickly to adopt new technologies. Second, the article assumes that incumbents have a monopoly on data. This is not necessarily the case. There are many ways for startups to collect data, such as through crowdsourcing or scraping the web. Additionally, the open-source nature of AI means that startups can access the same AI models as incumbents. Third, regulations will introduce its own impact on the progress/adoption. I expect the regulatory effects to more favour the unknown and dampen possibilities of a linear upside to incumbents And the article cites historical data to show that disruption has not accelerated significantly over the years. However, this data does not take into account the fact that the pace of technological change is accelerating. AI is one of the most disruptive technologies of our time, and it is likely to have a major impact on many industries in the coming years. Its also true that the big players of today wont try winning more with AI and as the adage goes, the faster one will adapt and succeed- "Its Game Even”

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