How Machine Learning Will Shape the Ecommerce Industry

With machine learning becoming ever more integrated into our daily lives, it’s natural to wonder, “How will machine learning affect ecommerce?”It’s a great question.

Machine Learning: The Future of EcommerceBefore we dig any deeper, it’s important to make a distinction between artificial intelligence and machine learning.

Let’s take a look at where ecommerce is at and how machine learning will affect ecommerce in the not-so-distant future.

Machine Learning and the Customer ExperienceMachine learning allows ecommerce businesses to create a more personalized customer experience.

A lot has changed in ecommerce over the last few decades and machine learning promises to change things even more.

How have you seen machine learning used in ecommerce?

ConclusionAs you can see, there are a lot of exciting opportunities for machine learning in ecommerce.

This article was summarized automatically with AI / Article-Σ ™/ BuildR BOT™.

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How AI is revolutionising drug industry by cutting pharmaceutical development time, says leading company

Founded by Alex Zhavoronkov in 2014, the enterprise uses AI and deep learning – a subset of machine learning that imitates the workings of the human brain in processing data – for drug discovery and ageing research.

Zhavoronkov says AI can speed up and reduce costs for drug development which – involving several phases of clinical trials, government approval and licensing – can last more than a decade.

“Moving to Hong Kong is the first step for us to go to China. The future for AI is in China as AI is about data and China has more data than any other country. The [Chinese] government also supports AI more than any other country,” he says.

With 66 staff, more than half of whom are deep-learning scientists, Zhavoronkov says they will hold a second round of private financing and a hackathon in Science Park later this year to recruit AI talent.

Zhavoronkov says AI can save up to “Two years in pharmaceutical research and development time”, and that the current development process is “Very inefficient”.

“The pharmaceutical drug discovery and drug development process consists of the many phases and often takes decades. The probability of failure is very high at every stage. In pre-clinical phases the failure rates are over 99 per cent and in human clinical trials about 90 per cent of the molecules fail,” he says.

“Western pharmaceutical companies are still very sceptical of the potential of AI and are not willing to change and upgrade. Fortunately, the Chinese government and companies prioritise the investment in AI and are very likely to enjoy the benefits and come up with innovative medicines faster.”

This article was summarized automatically with AI / Article-Σ ™/ BuildR BOT™.

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