The Hyperscale Revolution: Companies that are leading the way

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by Lindsey Francy Jan 29, 2023 News
The Hyperscale Revolution: Companies that are leading the way

The days of big data are over. The Hyperscale Revolution is a term used to describe the information flood around the planet.

The huge amount of data being generated is hard to comprehend. All you have to know is that it is doubling every 1.2 years. Since the beginning of the Pandemic in 2020, 90 percent of all the data has been created.

There is data all over the place.

In the morning, your smart toast will use a lot of power to get the shade of brown you want. Your egg tray will sync with your phone and let you know that you have four eggs left and each is fresh.

Tea-making is imminent and you need to boil just enough water for your mug.

By having a fried egg on toast and a morning cup of coffee, you can generate a few thousand kilobytes of data, before your smart car starts cranking out 25 megabytes of data per hour.

Drinking from a firehose

Hyperscale Revolution

Ultra-customized marketing, product enhancement and customer mapping are just some of the possibilities that can be found in hyperscale. Machine learning applications can run millions of simulations to improve efficiency and track consumer purchases.

It's a good idea to invest in a suite of data analytic gizmos. Picking the wrong one could give you the corporate equivalent of burnt toast.

It is like drinking from a firehose if you can't make sense of it.

It's not how much you know, it's how skilled you are at processing it into knowledge and then using it to your advantage.

According to a survey of business leaders by data specialists Ocient, the ability to rapidly analyze large datasets is linked with business success.

According to the survey, the world is moving beyond big data. Tomorrow's biggest businesses will need to perform continuous, complex analysis on those hyperscale datasets, using technology to run thousands or even millions of queries every hour.

Going hyper-local

According to Professor of Internet Governance and Regulation at Oxford University, a key success metric for companies is to realize that not all data is equal.

He told The CEO Magazine that conventional thinking says we need to collect lots of data from many different sources to capture reality and make good predictions. That is still focusing on the average situation.

In the future, businesses will need to avoid the temptation to generalize according to the author of the influential book.

We need to collect data from a specific individual and use that to give predictions to that individual. Data analysis leads to better predictions and decisions.

The hyperscalers

Hyperscale Revolution

What can we learn from the innovative data-driven models built by the following companies?

Adidas: Lakes and mesh

Once the preserve of pallid accounts staff in gray, windowless offices, data analytics became sexy as business leaders woke up to the potential of artificial intelligence.

Information technologists at its headquarters in Gurugram near Delhi enjoy an aesthetically pleasing workspace with intelligent spatial design, respite areas and punching bags.

Adidas was the first to embrace data-driven performance, both on and off the track, and pledged to invest $1 billion in research and digital transformation in the next two years.

Decentralizing its information warehousing and spinning it into a data mesh will be the key to that.

The director of platform engineering at Adidas said that the company has been successful in democratizing access to data. This is not the end of the journey. The first thing to do is detect and tackle bottlenecks that jeopardize the autonomy of different units.

Data lakes are different to warehouses as they contain raw, historical data for richer, more contextualized analysis.

Salesforce: AI that’s ethical

Einstein, the cloud software giant's ground-breaking artificial intelligence engine, was launched in 2016 to provide customer relationship management for pretty much any corporate need, and has been updated and improved every year since.

Rowena Westphalen tells The CEO Magazine that the company is at the beginning of an artificial intelligence transition from maximizing accuracy to the goal of inclusivity and responsibility.

Stakeholder capitalism and building trust will become critical components of these goals.

Barclays Bank: Voices of reason

The British banking giant was able to adapt machine learning into sophisticated cognitive reasoning that could be used for natural language processing by partnering with Simudyne.

IBM: AI in jeopardy

IBM first considered the idea of computer learning in the 1950s, but it was a stunt in 2011 that put it front of mind in the highly competitive space of artificial intelligence.

The two highest-ever scoring contestants in the TV game show "Jeopardy" were put against IBM's automated reasoning and natural language processing tool. It trounced them both and showed a previously unseen ability to process spoken language.

There was a debate on whether or not he was capable of thinking. It was able to process data at hyperscale and, before long, was being used by three-quarters of global banking institutions.

It was delivering more than one billion dollars in revenue to IBM, but it was still struggling to make a profit, putting its future in danger.

HUB24: Good advice for less

Four years after Australia's major banks withdrew from wealth management, an Australia financial services company found new ways to use artificial intelligence to cut the cost of financial advice and the resources required for compliance.

Had the banks been as generous with their data as HUB 24, they wouldn't have incurred such large losses.

The platform of the future is about using data and technology to powertransformational business solutions. The head of innovation said that the cloud is a key component.

SenseTime: Not losing face

The company that runs the world's largest artificial intelligence platform has recently applied its facial recognition software to detect defects in the car components sector.

Despite being blacklisted by the US government regarding security concerns and scrutiny over its alleged role in surveilling Uyghurs, it was able to roll out a successful initial public offering.

The company invests heavily in artificial intelligence to achieve carbon neutrality in emerging smart cities.

Meta: Well versed in data

Meta, the parent company of Facebook, is pouring unparalleled funds into new data technologies in order to conjure ever-more-sophisticated customer profiles for targeted marketing that others could only dream of.

Even though it has more personal customer data than any other entity, it still needs more training to spot harmful content.

Meta admitted that it didn't have enough reference points to allow its intelligence systems to quickly remove harmful videos such as the 2019!

Few other companies are pushing the deep learning limits in such a hard way. In September last year, he posted a 20-second Make-A-Video that was made entirely from short passages of text.

Neural networks that learn from processing billions of data points have been used to create automatically generated photo descriptions.

Hyping hyperscale

Hyperscale Revolution

There are many lessons to be learned about exploiting the Hyperscale Revolution.

When detailed customer mapping becomes an exercise in virtual stalking, that's when I ponder.

The ethics of enhanced artificial intelligence and surveillance capitalism are often brushed aside in the rush for ever more targeted marketing.

He told The CEO Magazine that many of the ways businesses and governments use data is inimical to humanity.

Artificial intelligence and advertising-funded social media data is damaging individual lives and undermines societal trust to the extent that democracy is threatened.

“Advertising-funded social media data and AI usage is destroying individual lives and undermining societal trust to the extent that democracy is threatened and scientific facts are denied.” – Barry Devlin

As corporations take every last drop of advertising revenue from your past, present and future, you are little more than the carcass of a life you once cherished as your own.

His book, Business unIntelligence, has been influential in the field of uncovering insights from hyperscale data, but he cautions business leaders not to want too much.

He says that big data was more hype than progress in business thinking. It is of limited value and may cause further problems for business and society.

Global businesses can find real value in better, broader information with deep understanding of its context.

Power to the people

There are plenty of conglomerates still mired in a swamp of outdated hardware, leadership and denial that they might be missing out on.

The information superhighway isn't the problem for many.

A survey of C-suite executives by NewVantage Partners found that the main hurdle was their people. Only a small percentage of people mentioned technology.

It's no wonder that the most in-demand skill of the year is artificial intelligence.

There are few jobs that don't use bigger data in some way. People have to be aware of both opportunities and dangers. If your enabled egg tray is working with the kettle to steal your identity, hyperscale should be on everyone's mind.

AI Warfare

Rival artificial intelligence platforms are analyzing real-time data to come up with a strategy to fight the war in Ukraine.

Every aspect of the conflict is related to the processing of enormous amounts of intelligence from thousands of sources.

He said that it can't be solved without the use of the latest weapons, modern intelligence, data transmission and destruction systems.

It takes less time for decisions to be made because the data is processed quickly. It's easy to control troops and weapons.