International Conference on Learning Representations (ICLR) and Consultative Group on International Agricultural Research (CGIAR) jointly conducted a challenge where over 800 data scientists globally competed to detect diseases in crops based on close shot pictures. The objective of this challenge is to build a machine learning algorithm to correctly classify if a plant is healthy, has stem rust, or has leaf rust. Wheat rust is a devastating plant disease affecting many crops, reducing yields and affecting the livelihoods of farmers and decreasing food security across Africa. The disease is difficult to monitor at a large scale, making it difficult to control and eradicate. An accurate image recognition model that can detect wheat rust from any image will enable a crowd-sourced approach to monitor crops. The imagery data came from a variety of sources.

Did you know around 87% of machine learning projects do not survive to make it to production? There is a disconnect between machine learning being done in Jupyter notebooks on local machines and actually being served to end-users to provide some actual value. Join Hamza Tahir, CTO at maiot who will aim to break down the key aspects of what sets machine learning apart from traditional software engineering, and how treating data as a first-class citizen is a fundamental shift in our understanding of complex production ML systems.

Omnichannel customer engagement solutions company eGain has added some great new features to its solution allowing third-party bots to better integrate into your contact center solution. At the same time, those who want a turnkey solution for conversational automation can activate eGain's Virtual Assistant. Conversation control can be handed off seamlessly across multiple bots and human agents while delivering a smart experience to consumers. "Consumers love messaging, but businesses continue to struggle with channel silos and point tools," said Ashu Roy, eGain CEO. "With eGain Messaging Hub, businesses can rise above the nitty-gritty to quickly deliver personalized, automated, messaging-based customer experiences across the enterprise."

Inside a Schnucks grocery store in St. Louis, Missouri, the toilet paper and baking ingredients are mostly cleared out. A rolling robot turns a corner and heads down an aisle stocked with salsa and taco shells. It comes up against a masked customer wearing shorts and sneakers; he's pushing a shopping cart carrying bread. The robot looks something like a tower speaker on top of an autonomous home vacuum cleaner--tall and thin, with orb-like screen eyes halfway up that shift left and right. A red sign on its long head makes the introductions. Tally freezes, sensing the human, and the customer pauses, seeming unsure of what to do next. Should he maneuver around the robot? Or wait for it to move along on its own?

Artificial intelligence is being enlisted in the fight against invasive plants, as experts try to design a system that makes problem species easier to track. Scientists from the UK Centre for Ecology and Hydrology (UKCEH) and Birmingham based company Keen AI are developing a new artificial intelligence system to quickly survey areas such as roadsides for invasive species of plant. Plants such as Japanese knotweed can cause damage in the UK, but finding and tracking their spread can be expensive and time-consuming, the experts said. The new scheme will use a high-speed camera on top of a vehicle to survey up to 120 miles of roadside vegetation a day. The images will be tagged with their GPS location and uploaded onto an online platform, where UKCEH ecologists will identify the plants in the photographs.

The space race of our time is the quest for domination in artificial intelligence. As a result, countries around the world are investing significant resources to build and mature their AI capabilities. They are also crafting strategic national plans about how and where to invest in AI. Taken together, these plans provide a snapshot of the global state of AI investments and how national governments are thinking about how to best utilize their resources. By studying 34 AI strategic plans of more than 1,700 pages, we have found that governments are failing to plan for operational investments, continue to be far more aspirational than practical in their planning, and are failing to consider funding realities.

Legend has it that when an emperor asked an inventor to name his reward, the inventor asked the emperor for payment in the humble grain of rice, giving the inventor the total gained by doubling a single grain of rice over a 64-square chessboard. In the end, the final squares had exponential mountains of rice. The velocity of technology advancement, especially for the manufacturing industry, is no different--it's exponential. Despite its lower digital maturity and research and development (R&D) investment than other industries,1 the manufacturing industry has been successful in gradually furthering its innovation agenda by increasing its patent-based innovation intensity to build new product and service capabilities. Continuous advancement will likely become critical to the success in an ecosystem that industry leaders believe is nearing the "second half of the chessboard."2

Verzeo is India's fastest growing company offering Certification based Internship programs in tech specialisations such as Data Sciences, Full Stack Web Development, Machine Learning, Cloud Computing etc We make this happen for each of our students by using our specially designed Artificial Intelligence-based software. We provide hands-on training, mentoring and live project support to engage in a transformational learning experience.

Every recession in the past and downturn in modern memory has led to the revolution of tech industry incumbents and the rise of new powers. The brutal recession of the early 1980s gave rise to the personal computer era. In the milder recession of the early 1990s, the federal government essentially handed the internet over to the private sector and laid the seeds for the dotcom boom that gave birth to Amazon, while Microsoft pulled off Windows' victory over Apple. The Great Recession of 2008-2009 hit the technology industry much less harshly than the rest of the economy. While the industry didn't experience any major setback, the downturn did propel the rise of social media in the form of Facebook and Twitter.

Who are the people driving the cutting edge of artificial intelligence, or AI as it is known? Where do the best of the best AI researchers come from and work? Neural Information Processing Systems (NeurIPS), considered the top AI conference, offers some answers. Its December 2019 meeting saw a record 15,920 researchers submit 6,614 papers, with a paper acceptance rate of 21.6 percent, making it one of the largest, most popular, and most selective AI conferences on record. Two things stand out from the reading of data collated from accepted papers.