Cisco has revealed plans to acquire San Jose startup Perspica to bolster the firm's previous purchase of AppDynamics in the data analytics arena. On Thursday, Cisco said in a blog post that Perspica is "the first acquisition to support and accelerate the AppDynamics vision." Financial details were not disclosed. The network equipment maker snapped up AppDynamics in January this year in a deal valued at $3.7 billion. AppDynamics is the developer of an enterprise platform suitable for monitoring application performance and business metrics.
The invention of artificial things that learn and perform actions took place in the classic times. Alongside Calculus Ratiocinator by Llull, there were many fictional stories and dramas depicting artificial things and their immense potentials. You must watch it if you haven't. Church-Turing thesis -- which means machines can simulate any process of formal reasoning (from Wiki). Theory that backed up the brains of creators like Allen Newell, Herbert Simon, John McCarthy, Marvin Minsky, and Arthur Samuel.
Earlier this year, Google CEO Sundar Pichai announced that Google was moving from mobile-first to AI-first. If the company is as successful shifting away from mobile as they were shifting towards mobile, the change could alter more than just Google. It will likely force other companies to change the way they operate in order to keep up. In much the same way that mobile-first required a new approach to strategy, design and development, AI-first will require a new perspective to properly benefit from its impact. Many companies will say they're "AI-first," but how many will truly be able to transform?
A survey of 500 chief information officers (CIOs) from around the world by ServiceNow has found that machine learning has arrived in the enterprise, and is making material contributions to everyday work. To realise its full value, technology leaders must find skilled talent to work side-by-side with machines, in addition to redesigning their organisations and processes. CIOs were interviewed in 11 countries across 25 industries, including 46 CIOs in the UK, to uncover the competitive benefits of adopting machine learning and hear how those leaders are driving results. See also: Government CIO I.T. budget breakdown: Gartner IDC estimates that investment in machine learning will nearly double by 2020, and recent analysis shows that machine learning specialists are among the fast-growing roles in IT. Humans are working side-by-side with smart machines for better accuracy, speed and growth of business.
Earlier this year, Cisco announced the acquisition of AppDynamics – uniquely positioning Cisco to enable enterprises to accelerate their digital transformations by actively monitoring, analyzing and optimizing complex application environments at scale. Today, we are excited to announce the intent to acquire Perspica, the first acquisition to support and accelerate the AppDynamics vision. In our experience working with the world's largest companies, we know that machine learning is only as good as the data it ingests; only as relevant as the data's timeliness; and only as valuable as the data's business context. Cisco's AppDynamics data sets span wherever the application components are deployed, and there is a massive opportunity to correlate this with user experience and business context. With the addition of Perspica to our AppDynamics capabilities, customers will be able to further take advantage of machine learning capabilities to analyze large amounts of application-related data, in real time and with business context, including when an application is deployed in a company's public, private and multiple cloud environments.
By 2021, early adopter brands that redesign their websites to support visual- and voice-search will increase digital commerce revenue by 30%. Gartner has found that voice-based search queries are the fastest growing mobile search type. Voice and visual search are accelerating mobile browser- and mobile app-based transactions and will continue to in 2018 and beyond. Mobile browser and app-based transactions are as much as 50% of all transactions on many e-commerce sites today. Apple, Facebook, Google and Microsoft's investments in AI and machine learning will be evident in how quickly their visual- and voice-search technologies accelerate in the next two years.
Just as oil propelled Standard Oil Co. Inc. to a position of dominant industrial power in the late 1800s, data is doing the same for a number of technology firms today. Half of consumer online spending in the U.S. is controlled by Amazon, a company that relies extensively on mining data so it knows what you want before your buy it. The list goes on, but one constant is clear. Just as oil spawned the growth of many industries, data is reshaping the technology stack. From robotics (think autonomous cars) to the entire field of data science, a new era of innovation is underway.
Artificial intelligence (AI) is the next technology to enter the hype cycle, and while it will most certainly have an effect on IT operations, the details as to how it will be implemented and how to generate a maximum return on investment are still unknown. At the moment, of course, the key challenge is overcoming the significant barriers to deployment, which include not only disruption to legacy architectures but to long-established business cultures as well. According to a recent study by Vanson Bourne on behalf of Teradata, a good 80 percent of enterprises are currently investing in AI, with telecommunications firms, professional and customer service providers and financial institutions leading the charge. While most outfits believe that the technology will produce significant ROI over the next decade, only about one-third see the need for additional investment over the next three years in order to remain competitive. At the same time, issues like the lack of advanced IT infrastructure and the need for AI-related skillsets in the workforce are seen as major barriers, as are the ever-present budgetary concerns.
Artificial intelligence is where the competition is in IT, with Microsoft and Google both parading powerful, always-available AI tools for the enterprise at their respective developer conferences, Build and I/O, in May. It's not just about work: AI software can now play chess, go, and some retro video games better than any human -- and even drive a car better than many of us. These superhuman performances, albeit in narrow fields, are all possible thanks to the application of decades of AI research -- research that is increasingly, as at Build and I/O, making it out of the lab and into the real world. Alexa and Samsung Electronics' Bixby may offer less-than-superhuman performance, but they also require vastly less power than a supercomputer to run. Businesses can dabble on the edges of these, for example developing Alexa "skills" that allow Amazon Echo owners to interact with a company without having to dial its call center, or jump right in, using the various cloud-based speech recognition and text-to-speech "-as-a-service" offerings to develop full-fledged automated call centers of their own.
There have been many "ages" throughout human history, most notably the industrial age and the digital age. Now, we have officially entered the age of artificial intelligence (AI). Within this AI age are many technologies, including machine learning and deep learning. These are fundamentally transforming and altering the business landscape. Its ability to revolutionize the world has been likened to what electricity did in its day.