Chinese enterprises increased patent filings for artificial intelligence products rapidly in the past couple of years. The companies holding the most active AI and machine learning patent families are now tech giant Tencent and search engine provider Baidu, ahead of U.S. firm IBM, South Korea's Samsung, Chinese insurance provider Ping An and former AI patent leader Microsoft. The latter company has been seeing one of its major AI investments come to fruition recently, as conversational AI bot ChatGPT by Microsoft partner OpenAI has been making waves. Microsoft swiftly announced another round of funding for OpenAI, rumored to be to the tune of $10 billion. As this chart based on the LexisNexis PatentSight directory shows, Tencent and Baidu became the largest patent owners in machine learning and AI in 2021, each holding more than 9,000 active patent families.
In many ways, 2022 has been a watershed year for software; with the worst ravages of the pandemic behind us, we can see the temporal changes and which ones have become structural. As a result, companies that used software to build a sustainable long-term business that disrupted the pre-pandemic status quo have thrived. Yet, at the same time, those that were simply techno-fads will be consigned to the dustbin of history. The software testing industry has similarly been transformed by the changes in working practices and the criticality of software and IT to the world's existence, with the move to quality engineering practices and increased automation. At the same time, we're seeing significant advances in machine learning, artificial intelligence, and the large neural networks that make them possible.
The past several months have been turbulent for Microsoft. In December, its $69 billion deal to acquire the video game maker Activision was challenged by regulators in the United States, and last week it began laying off about 10,000 workers. On Monday, Microsoft announced a major new investment in OpenAI, the start-up behind ChatGPT and other generative artificial intelligence breakthroughs, and signaled plans to include A.I. in an array of Microsoft products. The biggest slowdown came from Microsoft's personal computing business, where sales fell 19 percent and operating income fell 47 percent. The business boomed during the first part of the pandemic.
AI is a really fascinating tool if used correctly it can be beneficial especially for making money and doing work faster and easier. I hope that you all are familiar with ChatGPT and how people are using it every day in their daily tasks to ease the work. Now with the help of an AI, you can complete the job much faster which allows you more time and with this more time you can do many other things with it. One of the major fields is SaaS or Web Development now days we are seeing a lot of tools which are coving some kind of AI module in them, as said AI can be the next big thing and tests don't think of this as bitcoin or cryptocurrency which took place last year in 2022 and a lot of people lost their investment in it. Companies like Microsoft and Google are investing Billions of dollars in AI-related tools and now also a lot of other companies like Adobe are trying to include AI in their software.
Microsoft Azure is the leading SaaS or (Software as a service) platform with various functionalities for developers and creators. It is a popular platform for integrating with other available tools in the market. DevOps is a combination of two words; development & operations, with a tinge of QA (Quality Assurance) thrown into the mix. Together three terminologies make the word DevOps, which is quite the hit in IT & software circles. DevOps offers a quick and'agile' way of developing software, providing a coordinated front for developers and companies to manage their resources seamlessly.
The graph represents a network of 1,081 Twitter users whose tweets in the requested range contained "iiot machinelearning", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 04 February 2022 at 12:05 UTC. The requested start date was Friday, 04 February 2022 at 01:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 2-day, 21-hour, 2-minute period from Tuesday, 01 February 2022 at 03:57 UTC to Friday, 04 February 2022 at 01:00 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.
Deep learning models are wonderful, and we always want to use the newest cutting edge solutions to get the best results. But once in a while you stumble upon a relevant whitepaper that looks relevant to the task on hands, even though it's made a few years ago. And few years is an ethernity for the deep learning projects: old versions of frameworks, CUDA, python, etc -- nothing of that is easy to just install and laucnh on the modern systems. Usual answer for that would be Anaconda, but it doesn't provide enough isolation when it comes to the GPU accelerated models. My way of dealing with this problem would be of no surprise to the most: containerisation, in other words -- Docker.
This is a project that is organized by Datatalks.Club. In this competition, one has to train a deep learning model in tensorflow or pytorch to classify kitchenware items. I used tensorflow and keras for this task. As an image classification model, when given the image of one of the above-listed kitchenware items, the model will output probailities for each of the six classes. The highest probability serves as the model's final classification.