Guest post by Dr. Bhushan Desam, Global AI Business Lead, Lenovo Data Center Group
Artificial intelligence (AI) and machine learning technologies have turned the IT industry on its head, offering enterprises the ability to transform their approach to business strategy and customer insights, and research institutions to pursue humanity’s biggest challenges.
Once considered an abstract technology that was primarily championed by hyperscale companies (like Google, Microsoft, Baidu etc), it is encouraging to now see startups and larger enterprises alike across a variety of industries explore unique AI applications to solve business problems and scientific challenges. From assisting in healthcare diagnoses, to predicting when things like a jet engine is in need of maintenance, and assisting in crime prevention, the potential for innovation with AI is nearly endless. It’s even touching the average consumer’s daily life, as well: Facebook’s suggested photo tagging feature, for example, uses AI to recognize who’s who in your pictures.
Of course, AI does have its pain points and a key challenge for businesses today is the ability to differentiate between what’s hype and what’s reality. If you do a quick search right now, you’ll find tens of articles that include statistics about how many businesses leaders consider AI a fundamental part of their digital transformation or innovation strategies over the next several years. But adoption is still fairly low, and it’s this confusion around whether artificial intelligence is a viable technology that can realistically advance an enterprise’s bottom line that presents the biggest barrier to implementation.
At its core, AI is designed to create either greater effectiveness or efficiencies but there are two types of implementations:
- Narrow AI: only tries to solve one simple task or problem. In the Facebook example, AI can successfully identify someone (“This is Bhushan Desam”) but beyond that it doesn’t do much else. This will be more successful in the near-term.
- General AI: when computers have equal abilities as humans, and can understand human nuances such as context and reasoning to create solutions or take action while adapting to new situations. This kind of AI is still a distant vision and needs significant investment.
This confusion is often exacerbated by the fact that depending on the problem and ultimate end-goal, the way AI can be applied to that process can be dramatically different from customer to customer – and because of these two hurdles, many enterprises are hesitant to make large investments in AI.
This is where our team at Lenovo is uniquely positioned to help. As a company, we have developed an entire AI strategy, complete with a significant $1.2B investment in R&D, to help bring AI to life for our customers. One way we’re doing this is at three new AI innovation centers, where engineers, data scientists and experts from Lenovo and its partners, like Intel and NVIDIA, are available to work with customers and leading research institutions to fundamentally understand the business or scientific problem they want to address and identify ways in which artificial intelligence can further that goal. From there, we offer access to our AI innovation centers to provide the opportunity to test and refine their AI workloads before making an investment in AI-optimized hardware, software and services.
For example, our team recently visited an oil and gas company, which has miles and miles of oil pipelines to maintain and regularly monitor for leaks. The current process is highly manual, involving a considerable amount of driving and hiking to pipeline access points. Our team can work with this company to develop an AI-enabled drone to fly over the pipeline, and scan and process images to more quickly identify any potential leaks. We’re also working with North Carolina State University (NCSU) on critical research to conserve natural resources such as water and energy while meeting global food supply demand.
As Lenovo’s AI segment continues to grow there is certainly a lot to achieve but as a customer-centric company that strives to solve our customers’ biggest challenges, a fundamental part of our work over the next year will be soliciting feedback on these offerings and understanding how our AI solutions can help address real customer pain points.
With so many possibilities for AI, the future is promising – stay tuned in for more about Lenovo’s efforts to accelerate the adoption of artificial intelligence and our work with customers.
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