AI : The bottom line challenge

It's been nearly two years since ChatGPT burst onto the scene, ushering in a new era of artificial intelligence (AI) accessibility and capabilities. Since then, the AI landscape has evolved rapidly, with a proliferation of models, decreasing costs, and the integration of various modalities like voice and image recognition. It seems anything you do today is outdated tomorrow.

Amidst this whirlwind of progress, one fundamental need remains unchanged: the need for trust in technology that is rooted in its reliability and accuracy. As AI becomes increasingly integrated into our lives and businesses, it's crucial to separate the hype from the reality and focus on the practical applications that deliver tangible value.

The past couple of years have yielded valuable insights into the development and deployment of AI solutions. Two trends stand out:

• The Rise of Large World Models: Building comprehensive world models requires significant resources, not just in terms of computing power (GPUs) but also environmental impact.?
• No business really needs a world Model: However, the reality is that most businesses don't need a world model. They need targeted solutions that address their specific challenges and drive measurable business value. About a year ago, I wrote about the readiness of businesses to adopt generative AI.

Based on these trends and learnings, I think there are three key characteristics that will define successful AI solutions in the years to come:

• Ease of Use: The AI should be seamlessly integrated into the user's (reimagined) workflow, requiring minimal technical knowledge or expertise.
• Trustworthiness: The AI should consistently produce accurate and reliable results, with full transparency and traceability of its outputs.
• Financial Viability: The AI solution must deliver a positive return on investment, both in terms of the initial development costs and the ongoing operational expenses.

It is made to seem as though everyone needs to become a prompt-writing expert to leverage the power of AI. This is simply not true. Just as you don't need to understand the intricacies of design documents, IT architecture, or coding to use software, you shouldn't need to be familiar with prompts, vectors, LLMs, tokens, and contexts to leverage AI-powered tools.

Think about it this way: when you're shopping online, you don't need to worry about the underlying technologies like HTTP, TCP/IP, caching, and CDNs that make the experience possible. Similarly, AI should be seamlessly integrated into software products, hidden from the user's view but fully transparent and explainable to those who need to inspect its inner workings.

In terms of trust worthiness, most experienced professionals in any domain can "smell" inaccuracies in the outputs of a system and won't adopt it widely if it is not adequately accurate ALL the time. Most young professionals can't tell the difference and it would be dangerous to let them adopt such tools. Hence reliable accuracy is non-negotiable for wide spread adoption.

Moving beyond the hype surrounding AI, it's clear that the real business value will come from domain-centric, cost-effective, and easy-to-use solutions. Without getting into debates about artificial general intelligence (AGI), it is my view that businesses should focus on developing and deploying AI tools that solve specific problems and deliver measurable results.? This will only drive greater importance for and value from the adoption of domain-specific solutions.

For example, in industries like pharmaceuticals, biotech, and medical devices, AI has the potential to revolutionize multiple existing business processes around new product development, competitive intelligence, health economics and outcomes research, clinical trial design and many more such bedrock processes.?

For us at Pienomial we are constantly evolving our technology stack and expanding the functional footprint of our Knolens platform to serve a wider range of users in this domain in more valuable ways.??

If you are a professional working in or serving these industries, reach out to explore what we can do to change your trajectory of AI adoption and driven tangible bottom line benefits for your organization.