Artificial intelligence stocks are rarer than you might think. Many companies tout AI technology initiatives. But there really are few -- if any -- public, pure-play artificial intelligence stocks. And the AI competition landscape isn't an easy picture to paint. Instead, look for companies using AI technology to improve products or gain a strategic edge.

To support the demand for more smart applications for AI embedded system and application developers, Aetina offers a series of system on modules (SoMs) built with Nvidia Jetson modules. The company has compared its Nvidia Jetson AGX Xavier edge computing platform with the RTX 2080 graphics card. Using the Aetina Jetson AGX Xavier AI computing platform, which has 512 CUDA computing cores and 11 TFLOPS of AI computing inference, the company compared the Nvidia RTX 2080 high-performance graphics card which provides 20.14TFLOPS computing performance, but it needs 225W for operation. However, with the Xavier platform, it only cost 30W for operation, bringing 0.367 TFLOPS/W, for a four-fold improvement in AI performance effciency, reports Aetina, compared to RTX 2080's 0.09 TFLOPS/W. The Xavier platform supports various I/O extension, external high-speed Net card, and flexible match with different camera modules.

US semiconductor giant Intel has acquired Israeli startup Habana Labs, a developer of artificial intelligence processors, for $2 billion, the company announced on Monday. Founded in 2016, Habana Labs develops processor platforms that are optimized for training deep neural networks and for inference deployment in production environments. The company is headquartered in Tel Aviv and has offices in California, Poland, and China. Intel led a $75 million investment in Habana Labs in 2018. That year, Habana unveiled its Goya inference processor which it says is ideally suited for the most demanding AI applications in the industry, including private and cloud data centers, autonomous vehicles, factory and warehouse automation robots, and high-end drones.

Beethoven's unfinished symphony is set to be completed by artificial intelligence, in the run-up to celebrations around the 250th anniversary of the composer's birth. A computer is set to complete Beethoven's unfinished tenth symphony, in the most ambitious project of its kind. Artificial intelligence has recently been used to complete Schubert's'Unfinished' Symphony No. 8, as well as to attempt to match the playing of revered 20th-century pianist, Glenn Gould. Beethoven famously wrote nine symphonies (you can read more here about the Curse of the Ninth). But alongside his Symphony No. 9, which contains the'Ode to Joy', there is evidence that he began writing a tenth.

As algorithms become entrenched into society, the debate about their effects rages on. In essence, algorithms are sequences of instructions used to solve problems and perform functions in computer programming. As mathematical expressions, algorithms existed long before modern computers. While they vary in application, all algorithms have three things in common: clearly-defined beginning and ending points, discrete sets of "steps," and design meant to address a specific type of problem. On the one hand, algorithms play the role of prime suspect -- responsible for the recent UK pound's Brexit-induced flash crash, used for political and informational manipulation on social networks, and part of what Harvard Professor Shoshanna Zuboff calls "surveillance capitalism".

Founded in 2017 by tech entrepreneur Paul Hallett, experienced vet Robert Dawson and vet dermatologist Sarah Warren, the early-stage company is looking to bring vet care in line with some of the groundbreaking innovations seen in the human health sector. Vet AI recently partnered with pet insurer Animal Friends to offer its customers free access to its smartphone app. Called Joii, it lets owners check their animal's symptoms and receive instant advice from qualified vets on treatment through free online video consultations, which would usually cost £20 per call. Joii will advise users to visit a vet clinic if necessary, or it may decide that no action needs to be taken. The company has collaborated with a number of partners both internally and externally to develop its offering.

By 2030, consumers will be using a platform that not only intelligently manages their investments, but also incorporates their ongoing cash management into their advice and automation. You won't have to think about how much money you should keep in your checking or savings accounts. You shouldn't have to think about which account to pay your bills out of. We'll automate your entire financial life so you can spend more of your time doing the things that actually make you happy. As a result, we would expect to see things like budgeting tools and programs phased out.

Facial recognition technology became part of the fabric of life in China in 2019. Enabled by a vast network of cameras across the country, the government is using the technology for surveillance.

Honda is set to launch a partial self-driving car during in Japan the summer next year. Its Legend sedan will boast a Level-3 autonomy system, which enables the vehicle to pilot itself for extended periods. According to a report, the car will retail for 10 million yen, roughly $91,000, compared to 7.2 million yen for the current standard model. The news was first shared by Nikkei Asian, which discovered Hondo will incorporated the partial self-driving technology into the Legend, Honda's flagship luxury sedan. Because it will be fitted with the technology, the car will be 40 percent more expensive than the standard model.

The ever-growing volume of data of user-generated content on social media provides a nearly unlimited corpus of unlabeled data even in languages where resources are scarce. In this paper, we demonstrate that state-of-the-art results on two Thai social text categorization tasks can be realized by pretraining a language model on a large noisy Thai social media corpus of over 1.26 billion tokens and later fine-tuned on the downstream classification tasks. Due to the linguistically noisy and domain-specific nature of the content, our unique data preprocessing steps designed for Thai social media were utilized to ease the training comprehension of the model. We compared four modern language models: ULMFiT, ELMo with biLSTM, OpenAI GPT, and BERT. We systematically compared the models across different dimensions including speed of pretraining and fine-tuning, perplexity, downstream classification benchmarks, and performance in limited pretraining data.