What technologies helped business in 2018

2024 Author: Malcolm Clapton | [email protected]. Last modified: 2023-12-17 03:44

Collected only what really worked and was useful, and not just lit up in the headlines of technology news.

Every year, the authoritative MIT Technology Review publishes a shortlist of 10 BREAKTHROUGH TECHNOLOGIES 2018 of the main technological breakthroughs of the coming year. The heroes of the list are confidently leading in online discussions, author columns and futuristic news. However, not everyone is destined to quickly leave the laboratories and get into successful startups.

Last year's finalists included artificial embryos, sensory cities, deep learning convolutional generative adversarial networks (phew!), Headphone translators, carbon-free natural gas, predictive genetics, and a quantum computer. We chose three directions from the list of MIT and added one more from ourselves. The result is a list of technologies that really performed well in 2018.

Metal 3D printing

Sometimes it seems that 3D printing is like love: everyone talks about it, but almost no one has met. The reasons are standard: expensive, long, not entirely clear. Metal printing is even more specific: metallurgy is traditionally associated with large-scale industries.

Almost a year ago, Markforged energized the market with the launch of the first $ 100,000 3D printer that works with metal. Software with the use of artificial intelligence helped to reduce the cost of the production process. The metal parts that the printer prints have become lighter, stronger, and more complex in shape.

Another large manufacturer of such 3D printers, Desktop Metal, at the end of 2018 announced the release of two solutions at once: Studio System + and Studio Fleet. They are, in fact, "office options" of a 3D printer for small scale production.

This is what the "office version" of a metal 3D printer looks like. Three large drawers are the printer itself and two elegant stoves

Artificial Intelligence in the Cloud and Analytics for Business

Until recently, artificial intelligence seemed to exist exclusively among giant conglomerates like Amazon, Google, Microsoft. It's about money and other resources. The implementation of AI solutions requires significant expenditures on infrastructure capable of collecting and processing large amounts of data. To put it simply, business needs powerful hardware, and it still requires significant financial investments.

The process of "cheapening" artificial intelligence goes in several directions. The first is related to data: the more they become, the oddly enough, the cheaper they are obtained. Everyone seems to have come to terms with the fact that we voluntarily leave exabytes (that's a lot) of data on the Internet, registering in social networks and uploading videos to hosting. However, this is far from the only available source.

For example, ubiquitous video surveillance systems generate more traffic than YouTube.

CCTV cameras are the “eyes” of artificial intelligence. By themselves, they (like human beings) are not able to analyze what they see - for analysis you need a brain, in the case of AI - a neural network. And thanks to the development of cloud computing and services, it became possible to place this "brain" in the cloud, that is, in a remote data center.

When a business decides to contact a cloud service provider, the latter assumes the lion's share of the cost of working with equipment and data centers, providing the client with so-called box solutions (paid, downloaded the application, connected the service). The number and quality of cloud services reached their peak in 2018, so for deep learning, computer vision, video analytics and other areas related to AI, it became truly disruptive.

Video analytics helps, in particular, chain stores: for example, to record and prevent queues, determine when goods run out on shelves, and record violations in cash transactions. The necessary software is uploaded to the cloud, the camera connects to it and beeps if something is wrong. The availability of cloud services is increasing, so the service is becoming available to a supermarket, a chain coffee shop, and a small pharmacy.

Face recognition

One of the most "hype" technologies of the outgoing year by inertia continues to be associated with government control, Big Brother and spy thrillers.

Nevertheless, at the end of 2017, pilot face recognition technologies were launched How face recognition technology helps business and special services [large Russian retailers X5 Retail Group, Dixy and even Vkusville, which stands alone. And in 2018, for example, the Asna pharmacies joined them. World cases are even clearer: the Mariott Hotel and Alibaba Group in July 2018 launched a guest registration service based on facial recognition.

Businesses use facial recognition not only to track thieves, but also to increase customer loyalty: you can greet regular guests by name and offer bonuses.

Blockchain and personal data security

Blockchain has earned a reputation in the media as a technology that can be deployed almost anywhere. However, we have to admit that the distributed database will not get to small and medium-sized businesses so soon. But blockchain solutions focused on the protection of intellectual property are developing quite successfully, and for business in the creative industry, for example, this is very important. An example is Binded, a blockchain service for image copyrighting.

Blockchain is also promising for educational projects: MIT (Massachusetts Institute of Technology) students received their Digital Diploma debuts at MIT official diplomas directly on their smartphones through the Blockcerts Wallet blockchain application back in 2017. Digital diplomas and certificates registered with Blockcerts are protected from unauthorized access and are still available for sharing.

A related branch of blockchain solutions concerns the development of a verified portfolio for representatives of the creative profession. The first experiments with lists of career achievements and cases on the blockchain, for example, Indorse, are traditionally aimed at programmers. And Ledger Journal uses digital signatures and timestamps on the blockchain for scientific publications.