“Software is eating the world,” said Silicon Valley guru Marc Andreessen ten years ago. And he was right. Amazon, which could still be considered as a company focused on e-commerce and the sale of books, was already, in essence, a software company because of its innovative way of breaking down physical barriers and selling its catalog digitally through Kindle.
Ten years later, software itself is no longer the engine of innovation and social transformation that large technology companies seek with their products and services; it is artificial intelligence (AI). And we no longer speak of AI as something abstract, as something to be promoted and adopted by all companies and organizations without really knowing how, but rather the fundamental axis on which they are already making significant and tangible progress in our day to day.
AI as the new iPhone roadmap
A clear example is the iPhone, the most important technological product in the consumer market. During its first decade of renovations, all advances were made in software using hardware as a medium and with the aim of making it increasingly “transparent” to the consumer. With the launch of the iPhone X (2017), a new roadmap for the next decade of the iPhone was established, as noted by Tim Cook: machine learning algorithms and its processor with dedicated neural network hardware.
These AI algorithms began by making it possible for the iPhone to be unlocked by recognizing your face, being able to detect your attention at that precise moment and recognizing and learning from the physical changes it experienced over time. The iPhone software began to be designed not only to do certain tasks, but to act as a rational being that can obtain and compare information through the senses (the camera), use its memory and make a decision: unlock the iPhone or no.
Selective focus example during video recording on an iPhone 13 using “cinema” mode.
The most amazing feature announced at Apple’s annual event last Tuesday was the “cinematic mode” recording mode that replicates the frame focus effect commonly seen in any series or movie. The iPhone 13 is capable of switching during recording between foreground and background focus, and is smart to do so when the subject of the action is looking away from the phone. Once the sequence is recorded, the user can change the focus afterwards to play with the focus transitions and the times in which the subject moves to the foreground or background.
The room for improvement in hardware is already so narrow that it is increasingly difficult for phone manufacturers to encourage a terminal renewal: it is not enough to increase the speed of the processor, the resolution of the screen or the size of the battery, they are needed Hardware enhancements to bring software functions that rely on machine learning algorithms to life. Apple, which controls its entire ecosystem, from the design of the processor to the operating system and applications, has a clear advantage during this next decade of innovation as it did in the first decade of the iPhone.
Google will use its own chip in the new Pixel terminals to achieve what is impossible with the chips currently available on the market. We will see it in October, but it is clear where the shots are going to go in the next few years. The rest of Android manufacturers will have to follow this path, but they will do it dragging and trying to follow in the wake of Apple and, perhaps, Google. Google, pioneers in AI software and algorithms, needs to control its own hardware to unleash its advancements and deliver revolutionary solutions for everyday uses to its consumers.
AI is eating software
CUPERTINO, CALIFORNIA – September 14, 2021: Apple CEO Tim Cook with the iPhone 13 Pro Max and Apple Watch Series 7 during a special event at Apple Park. (Photo by Apple Inc.)
The paradigm has also changed if we look at it from a broader perspective. Progress is no longer subject only to the programs themselves, but to the use of computational power with an impact on the physical world such as the automotive sector, the development of more efficient renewable energy exploitation systems or health management. Software alone is no longer the tool on which to develop substantial advances for society. Software ate the world, but AI is eating software. And, unlike the advances we’ve seen over the past decade, those made in computational intelligence algorithms are closely tied to chip hardware and what we’re going to expect AI to control for us like cars or production robots.
Tesla is not a car manufacturer, nor is it a software company that also makes cars. Tesla is an artificial intelligence company that to offer something concrete has to manufacture cars and programs in a certain way. Like this one, all the major companies in the world are transforming themselves so that their products and services are controlled or enhanced by AI algorithms.
Amazon managed to transform its book-selling business through software. The AI is already devouring what until now was made by software, and this has just begun. Therefore, the most important thing in the future will not be the programmers, because programming a website or an application will soon be the task of AI services, but mathematicians who know how to direct, “feed” and develop machine learning algorithms, experts in ethics and treatment. of data, privacy experts and engineers who can devise the necessary hardware for the requirements of the AI dedicated to the tasks that the human being cannot cover.