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Her business mission is collaborating with the organizations to help them in taking innovation to the next level by transforming and rediscovering their core businesses with the help of Artificial Intelligence (AI) and Machine Learning (ML).

She set up her own company 'Numoit' to serve digital transformation and management consultancy to help companies grow revenue through digital solutions.

She leads Woman in Science chapters, provides mentoring for women in technology and her contributions has been recognised by leading universities and international foundations;

She says life is becoming more complex and AI helps us find optimal solutions that allow human beings to live better lives.

AI skills: 5 ways to build talent internally

As artificial intelligence use cases expand inside all types of businesses and industries, you can expect another sequel to a timeless IT hiring story: The Skills Shortage, AI edition – coming soon to a team near you.

As Pat Calhoun, CEO of Espressive, told us recently: “Most organizations want to embrace AI as part of their digital transformation but do not have the developers, AI experts, and linguists to develop their own or to even train the engines of pre-built solutions to deliver on the promise.” That’s a challenge, but it’s a familiar one for most IT leaders.

“Despite its evocative title, AI is remarkably similar to other fields in information technology, in that success comes through continuous learning, training, and great processes,” says Zachary Jarvinen, head of technology strategy for AI and analytics at OpenText.

] Jeff Reihl, EVP and CTO at LexisNexis Legal and Professional, expects this to be one of the key AI trends in 2019: IT shops investing significantly in developing AI skills internally, rather than hunting for purple squirrels – candidates who may not even exist – on the job market.

Reihl and other execs who are already doing this in their organizations describe a common foundation for success in building AI skills in-house: Give enthusiastic people opportunities to learn, and then give them opportunities to actually practice what they’re learning.

Consider their top advice: One reason you can encounter some cynicism about corporate training initiatives: Too often company leadership talks a nice game about continuous growth and learning, but they don’t tangibly carve out the time and resources for people to actually do so.

More than have our tech staff worldwide is now skilled in AI-related technologies.” Jim Johnson, senior VP at Robert Half Technology, notes that in addition to high-quality online courses in AI, in-person learning (including partnered with a local school) can happen both on-site or by sending people off-site for coursework.

One of the best ways to do this is to identify pilot projects that can actually improve a process or solve an existing problem, rather than doing projects that have no potential longer-term value or simply tinkering with new tools in a sandbox without any goals attached to the team’s experimentation.

The AI market is growing, but how quickly is tough to pin down

If you work in tech, you’ve heard about artificial intelligence: how it’s going to replace us, whether it’s over-hyped or not and which nations will leverage it to prevent, or instigate, war.

To make that point, here are just a few of the biggest rounds announced and recorded by Crunchbase in 2018: Now, this is the part I normally include a chart and 400 words of copy to contextualize the AI market.

We also know that Zymergen uses some AI-related tools to help it understand its data sets (check its jobs page for more).

In the spirit of transparency, CB Insights reports a 72 percent boost in 2018 AI investment over 2017 funding totals.

Crunchbase data pegs 2018’s AI funding totals at a more modest 38 percent increase over the preceding year.

But it’s increasingly clear to me after nearly two years of staring at AI funding rounds that there’s no market consensus over exactly what counts as an AI startup.

And the problem we’re encountering rhymes well with a broader definitional crisis: What exactly is a tech company?

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