Many fear that machines will replace human jobs. But, KEITH FENNER, Vice-President Sage Enterprise Africa & Middle East, says that it can offer enormous benefits to businesses, and that now is the time to invest in it.
Machine learning, which used to be something only computer scientists in server rooms discussed, has become a hot topic, along with big data and artificial intelligence (AI).
Machines develop algorithms that allow them to make predictions, such as the shows you might want to watch on Showmax or Netflix, to use a simple example. Machines will also update their models as new data is received, without human intervention.
Advances in machine learning have caused many to fear that machines will replace human jobs. However, I’d like to argue that it can offer enormous benefits to business, and that now is the time to invest in it.
Machine learning is all around us
Retailers can already successfully predict the performance of retail promotions using advanced machine learning. This not only maximises ROI, but also streamlines the inventory ordering process. Machine learning algorithms also enable effortless personalised marketing.
The financial services sector uses machine learning to detect fraud and provide pre-approved loan offers, while Google uses it to run its driverless cars. Brands use it to get a sense of what’s being said about them on social media.
The age of machine learning is here. In fact, 40% of businesses surveyed by the Accenture Institute for High Performance in a 2016 study are already using it to improve sales and marketing performance.
What machine learning offers to Enterprise
Machine learning is proficient at handling analytical tasks within defined parameters. For example, companies use machine learning to track new leads, upsells, and sales cycle times.
Elliot Yama points out that there is huge opportunity in what he terms “Quote-to-Cash” solutions:
· These encompass all the business processes involved in selling: from compiling initial offers right through to collecting payments.
· Quote-to-Cash solutions connect many previously manual tasks and disjointed processes, automating and optimising them seamlessly.
· They are now also helping to drive business outcomes across all sales channels and to optimise sales reps’ performance. For example, by improving quoting speed or the time it takes to generate a contract, machine learning can substantially improve salespeople’s chances of closing a deal.
But machine learning offers advantages beyond sales and marketing. It can be used to predict customer credit risk, to recognise text or speech (goodbye, painful data-capturing processes) and even to approve insurance claims quickly, without human intervention.
AI helps make work more meaningful
People will now have time to focus on other aspects of the business like driving innovation and exploring meaning. The beauty of machine learning is that it is able to do the work where humans can’t compete. A great example of machine learning at work is in the accounting industry.
AI can streamline accounting and compliance. It’s why we recently released Pegg, the world’s first accounting chatbot. Accounting is a perfect use case for automation, because it centres on repetitive, manual tasks. By using AI to automate it, businesses are able to focus more on core business activities and on the human elements of their business.
Huawei Mate 20 unveils ‘higher intelligence’
The new Mate 20 series, launching in South Africa today, includes a 7.2″ handset, and promises improved AI.
Huawei Consumer Business Group today launches the Huawei Mate 20 Series in South Africa.
The phones are powered by Huawei’s densest and highest performing system on chip (SoC) to date, the Kirin 980. Manufactured with the 7nm process, incorporating the Cortex-A76-based CPU and Mali-G76 GPU, the SoC offers improved performance and, according to Huawei, “an unprecedented smooth user experience”.
The new 40W Huawei SuperCharge, 15W Huawei Wireless Quick Charge, and large batteries work in tandem to provide users with improved battery life. A Matrix Camera System includes a Leica Ultra Wide Angle Lens that lets users see both wider and closer, with a new macro distance capability. The camera system adopts a Four-Point Design that gives the device a distinct visual identity.
The Mate 20 Series is available in 6.53-inch, 6.39-inch and 7.2-inch sizes, across four devices: Huawei Mate 20, Mate 20 Pro, Mate 20 X and Porsche Design Huawei Mate 20 RS. They ship with the customisable Android P-based EMUI 9 operating system.
“Smartphones are an important entrance to the digital world,” said Richard Yu, CEO of Huawei Consumer BG, at the global launch in London last week. “The Huawei Mate 20 Series is designed to be the best ‘mate’ of consumers, accompanying and empowering them to enjoy a richer, more fulfilled life with their higher intelligence, unparalleled battery lives and powerful camera performance.”
The SoC fits 6.9 billion transistors within a die the size of a fingernail. Compared to Kirin 970, the latest chipset is equipped with a CPU that is claimed to be 75 percent more powerful, a GPU that is 46 percent more powerful and an NPU (neural processing unit) that is 226 percent more powerful. The efficiency of the components has also been elevated: the CPU is claimed to be 58 percent more efficient, the GPU 178 percent more efficient, and the NPU 182 percent more efficient. The Kirin 980 is the world’s first commercial SoC to use the Cortex-A76-based cores.
Huawei has designed a three-tier architecture that consists of two ultra-large cores, two large cores and four small cores. This allows the CPU to allocate the optimal amount of resources to heavy, medium and light tasks for greater efficiency, improving the performance of the SoC while enhancing battery life. The Kirin 980 is also the industry’s first SoC to be equipped with Dual-NPU, giving it higher On-Device AI processing capability to support AI applications.
Read more about the Mate 20 Pro’s connectivity, battery and camera on the next page.
How Quantum computing will change … everything?
Research labs, government agencies (NASA) and tech giants like Microsoft, IBM and Google are all focused on developing quantum theories first put forward in the 1970s. What’s more, a growing start-up quantum computing ecosystem is attracting hundreds of millions of investor dollars. Given this scenario, Forrester believes it is time for IT leaders to pay attention.
“We expect CIOs in life sciences, energy, defence, and manufacturing to see a deluge of hype from vendors and the media in the coming months,” says Forrester’s Brian Hopkins, VP, principal analyst serving CIOs and lead author of a report: A First Look at Quantum Computing. “Financial services, supply-chain, and healthcare firms will feel some of this as well. We see a market emerging, media interest on the rise, and client interest trickling in. It’s time for CIOs to take notice.”
The Forrester report gives some practical applications for quantum computing which helps contextualise its potential:
- Security could massively benefit from quantum computing. Factoring very large integers could break RSA-encrypted data, but could also be used to protect systems against malicious attempts.
- Supply chain managers could use quantum computing to gather and act on price information using minute-by-minute fluctuations in supply and demand
- Robotics engineers could determine the best parameters to use in deep-learning models that recognise and react to objects in computer vision
- Quantum computing could be used to discover revolutionary new molecules making use of the petabytes of data that studies are now producing. This would significantly benefit many organisations in the material and life sciences verticals – particularly those trying to create more cost-effective electric car batteries which still depend on expensive and rare materials.
Continue reading to find out how Quantum computing differs.