On the first episode of the final season of HBO comedy series Silicon Valley, tech startup engineer Bertram Gilfoyle lets an AI version of himself take over his instant messaging duties. "Do you need the real me for this conversation?" he asks his colleague. It may sound extreme, but the existence of spellcheckers predates the personal computer by a decade. Since 1992, grammar checking has also come as standard in word processors. For the better part of a generation, we've been OK with robots watching and correcting our language, occasional run-ins with Clippy aside.

The University of Texas at San Antonio is participating in a pioneering program to introduce artificial intelligence (AI) principles to students in all academic disciplines. UTSA is working with MITRE, a not-for-profit corporation dedicated to research and development in the public interest, to help faculty develop lesson modules incorporating AI, big data analytics and data visualization in classrooms across campus this academic year. The project, codenamed "Generation AI Nexus" or "Gen AI," refers to anyone born in 1995 and later. The goal is to help all students, regardless of their major, understand AI and how to use it as an effective tool. "As an organization of system thinkers and problem solvers, MITRE recognizes the need for novel partnerships with universities to develop talent for the 21st century workforce," said Bobby Blount, department head for cyber ops and C2 effects at MITRE.

Ever since the industrial chemist Leo Baekeland began synthesizing phenol and formaldehyde in 1907, the world has developed a love-hate relationship with the resulting polymer: plastic. While plastic is convenient, durable, and cheap, 50% of all plastics (about 150 million tons every year, worldwide) are used only once and then thrown away. Even for those who dutifully recycle our plastic water bottles and sandwich bags, we're only tackling a small part of the problem. "Considering the size of the problem, there's relatively limited infrastructure in place to capture and treat stormwater," says Tony Hale, program director for environmental informatics at the nonprofit San Francisco Estuary Institute (SFEI). That's where SFEI is looking to use research and data--and most recently, drones--to make a difference.

See below for contact information.] Many innovative technologies have taken the world by storm, and one of the most exciting ones is artificial intelligence (AI). The adoption of AI is no longer a futuristic concept, and this technology is powering many tech solutions that we use on a regular basis. Without even realizing it, we've become dependent on these solutions that were created to make our lives easier. The growth of AI will continue to accelerate in the future.

We can already see the potential for artificial intelligence (AI) in international development: the seemingly endless possibilities to enhance productivity and innovation across healthcare, agriculture, education, transportation, and governance. Yet it is also becoming abundantly clear that AI could have negative repercussions as well, particularly in countries with weaker institutional capacity and legal protections. AI has the potential to threaten democratic processes, employment, human rights and -- because of the weaponization of AI tools -- privacy, policing, and defense. Apart from these potential benefits and threats, the transformative potential of AI for both good and harm will be magnified in the Global South, where existing gender and socio-economic inequalities could either be tempered or exacerbated. Given the opportunities and potential consequences of new automation and mechanization techniques and advanced analysis through machine learning and neural networks, IDRC is investing in applied research across a number of domains to advance the public good with the use of artificial intelligence for development (AI4D).

While Europe still faces a wide venture capital gap compared to Silicon Valley, the continent is nevertheless making big strides in positioning itself as an attractive hub for scientifically based startups. This is one of the key takeaways of "State of European Tech Report 2019," released today at the Slush technology conference in Helsinki, Finland. The report is produced by venture capital firm Atomico, along with Slush and London-based tech law firm Orrick. These "deep tech" industries span such cutting-edge technologies as quantum computing, computer vision, robotics, nanotech, and blockchain. Across these categories, European startups are on track to raise $8.4 billion in 2019, up from $6.7 billion last year and $3 billion in 2015.

Market Overview The AI image recognition market was valued at USD 1.41 billion in 2018 and is projected to reach a market value of USD 5.32 billion by 2024 at a CAGR of 24.7% over the forecast period (2019 - 2024). Image recognition technologies comprise voice, iris, palm, hand vein pattern, fingerprints, retina, hand geometry, facial pattern recognition, object identification etc. Image recognition based on these indications can be applied across various fields, such as vehicular safety, advertising, security and surveillance, biometric scanning machines, pedestrian recognition, and E-commerce. The adoption of artificial intelligence (AI) technology is rising, owing to its ability to enhance and automate operations and enrich the user experience. Governments are also focusing on increasing their AI capabilities to revolutionize various sectors, from healthcare to transport. EU has committed to invest EUR 1.5 billion in AI to catch up with the United States and Asia.

In countries like the US, artificial intelligence is already being used at a large scale to evaluate student essays, saving educational institutes money and time. According to reports, at least 21 states in America have deployed some type of automated scoring, from middle school to college level. Students are being graded on their essays using such AI systems designed by different vendors for highly important tests like the Graduate Record Examinations (GRE). While educators in the US say they are not going back to using human teachers for essay grading, it has received major backlash from parents particularly those from state school systems. But, it's not all great when it comes to automated grading.

Mainali's expertise is already being shared outside of the Chesapeake Bay watershed, including a project concerning water flow management in Colorado in an area where water is a scarce resource. To help manage the demands of water for agriculture and wildlife, Mainali wrote algorithms that optimize the water flow and release from reservoirs by various agencies. These algorithms will be used for informed decision making about sharing the responsibility of water release from multiple reservoirs on a daily basis.

Hardware, specifically designed for machine learning accelerate training and performance of neural networks and reduce the power consumption. Country: UK Funding: $310M Graphcore is a semiconductor company that develops accelerators for AI and machine learning. It aims to make a massively parallel Intelligent Processing Unit that holds the complete machine learning model inside the processor. Wave Computing is developing the Wave Dataflow Processing Unit (DPU), employing a disruptive, massively parallel dataflow architecture. When introduced, Wave's DPU-based solution will be the world's fastest and most energy efficient deep learning computer family.