The AI Balancing Act: Merging Old and New to Generate World-Class Social Insight

How Buzz Radar Combines AI Approaches for Pharmaceutical Industry Solutions

It's been interesting watching the AI revolution unfold over the last few years. We've gone from a time when AI felt like something fairly niche that required some pretty specific tech knowledge to the point where it sometimes feels that everyone has added "AI expert" into their LinkedIn bio.

We've been using AI tech in various ways since Buzz Radar was founded back in 2012, and for a while it felt like a very niche area of technology, at least in the world of social data and sentiment analysis — a corner of the tech universe we'd adapted for ourselves.

But in the last two years AI leapt forward in capability. What we, until recently, thought was science fiction is now absolutely mainstream and is quickly becoming an essential part of everyone's daily working lives.

As the technology evolves and becomes more embedded into our businesses, understanding the distinctions between different types of AI models and the roles they play is becoming increasingly crucial.

At Buzz Radar, we've been integrating innovative AI into our work for over a decade, applying both discriminative and generative AI to deliver data and insights in pioneering ways.

When we look back at the last decade - from our early experiments in 2012 to the cutting-edge solutions we're developing now in 2024 - it's clear that our instincts have always been good, committing to doing things the right way, with a solid scientific foundation. It's this approach that's helped us make our mark, especially in high-stakes industries like pharmaceuticals where there's no room for guesswork.

The Early Days: Discriminative AI and Its Impact on Social Listening

Back in 2012, the AI landscape looked vastly different. Most AI applications were built on what we call discriminative AI. These models were capable of understanding and sorting things into categories, and they excelled at tasks like figuring out whether an email was spam or not, or determining if a customer review was positive or negative.

At Buzz Radar, we saw the potential in these models early on and they became a cornerstone of our work, using discriminative AI to build tools that could sift through mountains of data and produce actionable insights for businesses. This technology effectively functioned as a high-speed analyst, identifying trends and patterns at a scale impossible for human teams.

Plot Twist: Enter Generative AI for Social Intelligence

Fast forward to early 2023, and the AI world was buzzing with a new star: generative AI. If discriminative AI was about sorting ingredients into different buckets, generative AI, like OpenAI's game-changing ChatGPT, could create something entirely new from existing information.

We saw generative AI as the perfect complement to our existing tools. While our discriminative models were busy categorising and analysing, our new generative models could take those insights and transform them into creative new ideas and solutions.

The Best of Both Worlds: Our Integrated AI Approach

What we find is that things get truly interesting when you start combining these approaches. We didn't just adopt these two types of AI - we made them work together in a way that's uniquely Buzz Radar. The result? BRIANN (Buzz Radar Insight Analyst Neural Network), our AI solution built specifically for the pharmaceutical industry.

BRIANN combines multiple AI capabilities working in concert:

• First, BRIANN functions as a data analyst (that's our discriminative AI). It examines vast amounts of online conversations, social media posts, and discussions, identifying patterns in what's happening in the pharmaceutical landscape.
• BRIANN is also an insights generator (that's the generative AI). It takes all those analysed data points and uses them as the foundation to develop fresh insights, predict emerging trends, and create meaningful content.
• The key innovation is that BRIANN integrates both of these functions into a single system: combining analytical precision with creative intelligence to generate insights and solutions that neither approach could produce independently.

For Buzz Radar, integrating generative AI into our platform was a natural progression. We recognised that while discriminative AI could provide accurate classifications, generative AI could enhance these insights by uncovering deeper patterns, generating predictive models, and offering creative solutions to complex problems.

This combination of discriminative and generative AI allows us to deliver more accurate, useful, and innovative insights to our clients. Pharmaceutical companies, in particular, require AI solutions that are not only cutting-edge but also grounded in robust scientific principles. Our roots in discriminative AI highlight our ability to deliver precise, reliable insights, while our advancements in generative AI showcase our capacity for innovation and creativity.

Looking Ahead: The Future of AI in Pharmaceutical Intelligence

Our journey from discriminative to generative AI, culminating in BRIANN, has been transformative. But continuous innovation remains essential. As advances in AI accelerate and the pharmaceutical industry evolves, standing still is effectively moving backward.

We're committed to staying at the cutting edge, continually refining and expanding BRIANN's capabilities. Our goal is to keep providing our pharmaceutical clients with insights and solutions that aren't just innovative, but grounded in solid science and real-world data.

For our clients in the pharmaceutical industry, this approach means consistently staying ahead with insights that are as scientifically robust as they are creative and forward-thinking.

Contact us today to discuss how BRIANN can be integrated into your current workflows and transform your pharmaceutical social intelligence capabilities.

Patrick Charlton Published on September 17, 2024 12:09 pm