FountainBlue's February 16 VIP Roundtable was on the topic of 'Leveraging AI to Facilitate Innovation'.
Our executives in attendance represented a wide range of backgrounds, industries and roles. They collectively remarked on how quickly technology is advancing and how broadly AI solutions are being applied in practical ways to facilitate innovation, to improve decision-making, to support problem-solving, to optimize productivity, to raise quality standards, and to provide other business benefits.
Our executives remarked on the noteworthy technology advances which have occurred/ are happening to address the rising demand for AI solutions, including ChatGPT and Large Language Models (LLMs). This includes the fact that chip-to-chip interconnections are becoming more complex, including clusters of multiple GPUs running in parallel.
Our executives also asked many questions including:
How do existing hardware and software solutions address the need for low latency and low power usage when so much data needs to be processed?
How do we optimize storage, organizing for short term, medium term and long term access, real time
How can software solutions help support the hardware advances around memory?
Granted, there are policy, ethical, bias and other challenges ahead as AI inevitably broadens and expands, but the shift is already happening, so forward-thinking leaders and companies must put guardrails in place and take progressive steps toward applying AI solutions to meet specific business needs.
Below are some examples of how AI is leveraged to facilitate innovation:
providing real-time quality checks on manufactured goods, to ensure conformance to quality standards, with clear definitions of faulty or unacceptable defects
creating real-time language translation solutions
supporting engineers with code creation, code review, debugging
ensuring data quality/validity, resilience/protection, availability/access
optimizing power availability based on individual power usage patterns
coordinating access to data by multiple applications
generating ideas and encouraging divergent thinking
designing prototypes based on customer criteria and past models
compiling records of multiple formats into a common system for more efficient vendor (or customer or employee) management
automating calls and emails
creating original content/materials based on predefined criteria and objectives
researching reports, history, data to inform business and product decisions
conducting AB product and marketing testing to better understand market needs and interests and to understand what works and doesn't work for which audience(s)
The bottom line is that AI has the potential to take away the mundane, repetitive tasks more quickly and more accurately. When leveraged well, looking at the big picture and putting guardrails in place, humans can potentially more efficiently deliver on the business needs, in partnership with a wide range of AI solutions.