Tamil Nadu Agricultural University (TNAU) announces that it has partnered with NCE Laboratories India for developing solutions to detect crop diseases using artificial intelligence and machine learning.
TANU and NEC Laboratories recently signed a memorandum of understanding to establish this collaboration.
According to a release, NEC seeks to help identify illness and deficiency categories and give cures through agricultural experts under the terms of the MoU.
NEC plans to develop an artificial intelligence-powered smartphone application, while TNAU would provide expert advice and assist in data collection to diagnose diseases. The signing of the MoU was witnessed by NEC Laboratories India senior vice-president and head Keiji Yamada, TNAU Registrar and acting vice-chancellor A S Krishnamoorthy, and senior officials from the Center for Plant Protection Studies.
Keiji Yamada said, “We are proud to be partnering with TNAU in new ways of applying AI and analytics to resolve crucial issues in agriculture in real-time.” He further added that this collaboration is vital and relevant since India is also one of the world’s major food producers, in addition to being a predominantly agricultural society.
The combined expertise of both entities in their respective fields will be crucial in developing artificial intelligence solutions for the challenge of crop disease detection.
The United Nations claimed that farmers across the globe lose nearly 40% of their produce due to diseases and insects which infect plants. The agriculture industry in India is burdened with the challenge of crop losses of 30-60%. Diseases (15-25%), soil nutrient shortage (36.5%), insects, and pests, which reduce crop output by 10-40%, are the primary causes of loss.
Therefore, the technology jointly developed by TNAU and NEC Laboratories will considerably help farmers minimize their losses by detecting diseases at a very early stage and aid in taking measures.
Actionable and quantifiable analytics solutions providing company Tredence announces that it has opened new AI delivery and R&D centers in India to strengthen its presence in the country.
The company said it had launched its new centers in cities including Bengaluru, Gurugram, and Chennai. The AI delivery and R&D centers will become fully operational by May 2022 and will have an initial capacity of 1400 seats.
Over the last year, Tredence has doubled its workforce in the country and has promised to hire nearly 500 more by the end of 2022. Through the new delivery centers, Tredence will provide advanced analytics, data engineering, and data science solutions to retail, CPG, TMT, industrial manufacturing, and healthcare clients around the world.
CEO and Co-founder of Tredence, Shub Bhowmick, said, “Expanding our reach into new talent markets is a critical component of our growth plan. We plan to do so by constantly looking for top-tier talent in new regions and partnering with premier institutes like IIT Madras to focus on training and talent development.”
He further added that opening the company’s new offices is a step towards Tredence’s goal of assisting employees specializing in legacy technologies to modernize by providing them with data science and data engineering opportunities. Tredence was named a Great Place to Work-Certified company in India earlier this year, confirming its inclusiveness and openness.
United States-based analytics solutions provider Tredence was founded by Shashank Dubey, Shub Bhowmick, and Sumit Mehra in 2013. The company specializes in offering actionable and quantifiable analytics solutions to marketing, sales, and operational issues with a broad industry focus, strong advanced analytical skill sets, and deep domain expertise.
“Expansion and addition of new India delivery centers signifies an exciting chapter for Tredence as we continue to build groundbreaking data science solutions for global industries. Setting up new delivery and talent centers in India reflects the momentum we are experiencing in the market and aligns with our growth imperatives,” said Chief Operating Officer of Tredence Harish Gudi.
He also mentioned that cities like Bengaluru, Chennai, and Gurugram are excellent places to start for tech companies trying to improve AI innovation and distributed agile delivery models.
Ai-Da, a novel robot developed by English gallerist Aidan Meller and Cornish robotic business Engineered Arts, is the world’s first artificial intelligence-powered robot that can paint just like an artist.
The developers of this robot claim it to be “the first ultra-realistic humanoid artist.” Ai-Da was first introduced back in 2019 at Oxford University, after which it has traveled across the world to showcase its capabilities.
Recently in 2021, Ai-Da also displayed her artwork at the Design Museum located in London. The robot has a robotic arm with which it can create stunning paintings, a realistic-looking face structure, along with eyes that can scan the surroundings and also blink like humans.
“We haven’t spent eye-watering amounts of time and money to make a very clever painter. This project is an ethical project,” said the developer of the robot, Aidan Meller.
AI algorithms lead Ai-Da to probe, pick, make decisions, and, eventually, create a painting, with her camera fixated on her subject. The developers say that Ai-Da can not only paint but can also sculpt, sketch, and even write poems.
As artificial intelligence is an evolving technology with breakthroughs each year, Ai-Da also gets updated regularly, which helps in expanding and further refining its capabilities.
While the AI-powered robot has not yet been able to create entirely unique pieces of art, her five-hour method from start to finish ensures that no two paintings are the same. Ai-Da’s new painting style was introduced before her solo exhibition at the Venice Biennale in 2022, which will open to the public on April 22.
“Ai-Da Robot, as technology, is the perfect artist today to discuss the current obsession with technology and its unfolding legacy,” added Meller.
Meta is currently hiring a Postdoctoral Researcher for its Facebook AI Research (FAIR), a research organization focused on making fundamental progress in AI.
According to Meta, its Facebook AI Research (FAIR) conducts cutting-edge research to advance the state-of-the-art and deepen the company’s understanding of existing AI approaches. Meta is hiring for one-year fixed-term Postdoctoral roles in multiple locations across the globe.
The selected candidate will collaborate with the supervisor and other researchers at FAIR to establish and implement a research agenda and publish world-class research.
The position involves research in multiple fields such as AI, ML, computer vision, natural language processing, Speech & Audio, Conversational AI, Theory, Reinforcement Learning, Robotics, and many others.
Meta says that the selected candidate will gain not only significant experience at a top-tier research institute but also the chance to publish scholarly articles regularly and establish a global reputation.
Key job responsibilities include presenting high-quality papers and researchers at conferences, writing and debugging research codes, designing and implementing experiments to test research ideas, and several other related tasks.
Ph.D. degree holders or individuals who have completed a postdoctoral assignment in Computer Science or a similar field with a background in AI/ML and have experience in C/C++, Python, C# can readily apply for this position at Meta.
However, candidates with first-authored publications at peer-reviewed conferences will be preferred. Interested applicants can submit their applications through the official website of Meta. The company will conduct interviews in three windows starting from March and will continue till October 2022.
Conversational messaging platform providing company Gupshup acquires Active.ai, a leading conversational AI provider for banks and Fintech companies.
The acquisition will help Gupshup further strengthen its expertise in customer experience for its clients, especially those involved in the BFSI industry. However, no information has been revealed by either of the companies regarding the valuation of this acquisition deal.
In addition to this acquisition, Gupshup is also in talks with possible investors about raising $100 million to $200 million in pre-IPO fundraising. Last year in July, Gupshup raised $240 million in its additional funding round, which witnessed participation from investors such as Tiger Global, Fidelity Management, Think Investments, Malabar Investments, Harbor Spring Capitals, and White Oak.
During the funding round, Gupshup officials said that the raised capital would be used to expand the company’s market reach and to develop its business messaging platform further.
Co-founder and CEO of Gupshup, Beerud Sheth, said, “Active.Ai’s robust CBaaS platform adds more vertical depth to our product stack, giving BFSI customers the tools to create intelligent, frictionless micro conversations with consumers using voice, video and messaging channels.”
He further added that they are excited to welcome the Acitve.Ai team to the Gupshup family and look forward to leading the next wave of conversational engagement and commerce technologies.
Singapore-based artificial intelligence company Active.ai was founded by Parikshit Paspulati, Ravi Shankar, and Shankar Narayanan in 2016. The company is known for building an advanced, patented conversational AI platform for financial institutions, insurance firms, and capital markets that can be quickly deployed.
Axis Bank, Kotak Mahindra Bank, Tata Capital, IndusInd Bank, and HDFC Securities Ltd in India, NTUC Income, NIUM, and Tonik Bank in Southeast Asia, and Abu Dhabi Commercial Bank PJSC (ADCB), Qatar Islamic Bank, and Burgan Bank in the Middle East are among Active.ai’s most notable customers.
“In the conversational economy, business to consumer engagement that combines advanced natural language processing with deep enterprise connectivity is essential. Active.Ai’s conversational engagement platform powers leading financial enterprises across 43 countries,” said Co-founder and CEO of Active.ai, Ravi Shankar.
Global technology giant IBM announces the launch of its all-new z16 system aimed for transaction processing at scale and the industry’s first quantum processing system.
According to the company, the launched technology is IBM’s next-generation system featuring an on-chip artificial intelligence accelerator that provides latency-optimized inference.
The IBM z16 will allow customers to analyze real-time transactions at scale for mission-critical workloads, including credit cards, healthcare, financial transactions, and many more.
In addition, the chip is specifically designed to help protect against possible threats that may be used to crack today’s encryption technologies. The chip can process 300 billion inference requests per day with just one millisecond of latency, allowing financial institutions to considerably boost the analysis speed of detecting fraud during transactions.
Senior Vice President of IBM Systems, Ric Lewis, said, “IBM is the gold standard for highly secured transaction processing. Now with IBM z16 innovations, our clients can increase decision velocity with inferencing right where their mission critical data lives.”
He further added that this creates enormous opportunities for clients to change the game in their respective industries, putting them in a better position to deliver better customer experiences and more powerful business outcomes. Organizations can effectively increase their resiliency to present and future cyber threats using IBM z16 quantum-safe cryptography.
IBM claims that its z16 incorporates new artificial intelligence acceleration through an on-chip AI coprocessor to reduce latency and deliver exceptional performance for in-transaction inference.
The IBM z16 combines AI inference via its IBM Telum Processor with highly secure and reliable high-volume transaction processing. Apart from banking, the newly launched processor can also help multiple other industries to carry out tasks such as loan approval, clearing & settlement, federated learning for retail, etc.
In-game asset and virtual world marketplace Fractal raises $35 million in its recently held seed funding round led by Paradigm and Multicoin Capital.
Multiple investors such as Andreessen Horowitz, Solana Labs, Animoca, Coinbase Ventures, Play Ventures, Position Ventures, Zynga founder Mark Pincus, Crossover, Shrug Capital, and others participated in Fractal’s latest funding round.
The company plans to use the fresh funds to extensively hire new engineers and game developers and grow a GameFi participants’ ecosystem. The platform developed by Fractal was recently launched for the public in December 2021.
Matt Huang, co-founder and managing partner at Paradigm, will join Fractal’s board as part of the funding. “We’re in the middle of a generational shift in gaming, powered by crypto, where players expect a greater degree of ownership and control of their digital items,” said Huang.
He also mentioned that Fractal’s competent team understands this shift better than anyone else, and he is delighted to invest in the company’s vision.
United States-based virtual marketplace providing startup Fractal was founded by Justin Kan, Mike Angell, and Robin Chan in 2021. Soon after its establishment, the company developed a virtual world marketplace where users may find, purchase, and sell gaming NFTs.
The company also launched its new product named Fractal Launchpad, enabling gaming creators to sell their initial NFT collections to the general market. Some of the notable games launched through Fractal’s platform include House of Sparta, Tiny Colony, Yaku, and several others.
Game developers can now start applying on Fractal’s website to list their NFTs on the marketplace.
Co-founder of Fractal and Twitch, Justin Kan, said, “NFT marketplaces are still the wild west right now, with many teams failing to deliver on their promises. We are working with the best AAA gaming studios with large communities to bring the coolest game experiences to players. The transition to blockchain assets is a new business model for gaming, and in 10 years will be an even bigger shift in the gaming world than Twitch was.” He further added that the company aims to onboard more than 100 million cryptocurrency users through blockchain games.
The AI technology will use over 2500 CCTV cameras installed across the city to recognize helmet-less bike riders and parking violations. Nearly 125 CCTV cameras can recognize the number plates of vehicles out of the lot. After scanning, the system will then process the complaint and send it to violators, which, if done manually, would consume a lot of time.
Officials said the technology would be connected to the RTO server so it can send e-challans to violators of traffic laws through SMS in real-time.
Additionally, the system will also lessen the risk of police personnel being injured while physically halting criminals. Kolkata Police revealed its plans to use this AI system back in November 2021 and had requested a session with experts to understand the functionalities and capabilities of the AI surveillance system.
A senior police official said, “The vendor set up its system at the traffic control room last week. A few senior officers have now been tasked to prepare daily reports on the efficacy of the system and provide a proper demonstration of the system. This will be a major indicator on how we go about integrating AI in the city’s traffic system.”
Kolkata Police was approached by two companies to deploy their AI surveillance systems. However, Kolkata Police asked the companies to install their software in the control room for them to test.
Alphabet’s self-driving technology developing subsidiary Waymo showcases its new autonomous driving tech in the streets of San Francisco, United States.
The newly demonstrated technology of Waymo now allows the company’s robotaxis to operate autonomously without the need for any human intervention or driver on board. Waymo also released a video showcasing the functioning of the robotaxi.
Though Waymo had been testing its robotaxis since last year in the region, it earlier had to deploy a safety driver in the taxis as a precautionary measure to avoid any mishaps on roads and ensure the safety of the passengers.
Waymo has reported that one of its specially equipped self-driving Jaguar I-Pace robotaxis has driven in San Francisco for the first time without a human driver. Waymo employees and members of the company’s Trusted Tester program can enjoy the one-of-a-kind experience of commuting in a fully autonomous taxi.
CEO of Waymo, Tekedra Mawakana, said, “We’ve learned so much from our San Francisco Trusted Testers over the last six months, not to mention the innumerable lessons from our riders in the years since launching our fully autonomous service in the East Valley of Phoenix.”
He further added that the tests had a direct impact on how they are bringing their service forward as they welcome the first employee riders in San Francisco.
According to the company, its autonomous taxis will be operating within a designated route that stretches from Presidio to Candlestick Point. This location will be expanded further in the future as Waymo did in other testing areas.
Since the advent of artificial intelligence (AI) as a theoretical concept or a movie trope, the technology has progressed leaps and bounds, accommodating every primary industry’s needs. Be it finding the protein structure of genetic disorders, recommending our next binge, or ensuring streamlined claims processing; artificial intelligence has transformed most of the sector. However, while the rapid adoption of its technologies fuel disruption and innovation, there has been immense demand for professionals with AI expertise to push such changes. This resulted in the software sector lagging behind due to the scanty availability of candidates that fit the job descriptions. Imagine the few percentages of people with coding skills designing AI solutions that possess the power to revamp our world with its offerings. This void in the job market led to the growth of no-code AI platforms and tools.
Meanwhile, because coders make up such a tiny fraction of the population, the software they create risks being inherently discriminatory and biased. A diversified staff is necessary to avoid racial and gender prejudice in AI products. Not only that but people with disabilities should be included in the application design process to make it accessible. However, understanding how to code generally necessitates a higher education, and access to this knowledge is thus another obstacle to inclusion. Further, the scarcity of an adequate talent pool creates fierce competition among different industry niches to hire the ‘qualified’ by luring higher pay; thus widening the gap between demand and availability. These bottlenecks are also addressed when no-code platforms offer to fill the vacuum by enabling anybody to create an app. Most of these non-code tools have a visual appeal that allows even non-coders to develop AI-based solutions.
No coding-backed solutions have made it easier for individuals and businesses to experiment with artificial intelligence areas like data science or technologies like machine learning. These tools let organizations deploy AI models quickly and inexpensively, allowing their domain experts to benefit from them. At the same time, it has also reduced development time by a huge margin. Earlier the process of developing proprietary AI solutions involved writing code, cleaning data, classifying, organizing data, training, and debugging the model. This takes a lot longer for people who aren’t familiar with data science.
The new no-code platform can now uncover new insights and help build predictive models faster thanks to a refined user interface and integrated approach. For instance, in data analytics, no-code platforms can employ various data sources to test millions of hypotheses to identify previously unknown market drivers and restraints, and scenario outcomes. Then they can explain the findings in human-readable language or visual format – all without the use of code and in an automated manner. No coding platform, such as the DataRobot app builder, is used to create artificial intelligence and robotics applications. Without requiring any code, the platform allows users to instantly transform any model into an AI or robotics application for end customers.
Because of the rising skill scarcity, no-code platforms are likely to become more popular in the future years, with Gartner estimating that by 2023, 65 percent of app development would be low-code/no-code.
Nenshad Bardoliwalla, chief product officer of DataRobot, recently spoke with TechTalks about the difficulty of serving the demands of machine learning and data science in various industries, as well as how no-code platforms are democratizing artificial intelligence. DataRobot and other no-code AI platform providers, according to Bardoliwalla, are developing tools that allow domain experts and business-savvy people to create and deploy machine learning models without having to write code. Users can submit datasets to DataRobot, complete essential preprocessing procedures, choose and extract features, and develop and compare a variety of machine learning models, all through a user-friendly graphical user interface.
Bardoliwalla points out that until almost a decade ago, an organization’s ability to query data and generate reports was confined to a few employees with the expert coding skills required to maintain databases and data warehouses. However, today’s tools have progressed to the point where non-coders and non-technical persons can conduct the majority of their data querying jobs using simple graphical tools without the need for experienced data analysts. Bardoliwalla assures that no-code AI is not a replacement for the expert data scientist. However, it enhances machine learning productivity across the organizational spectrum, allowing more individuals to fabricate AI-powered models. This alleviates much of the responsibility on data scientists’ shoulders and allows them to refocus their talents on other crucial tasks.
Apart from DataRobot, no-code AI services like Akkio, Obviously.ai, Levity, Clarifai, Amazon SageMaker, Peltarion, and Veritone, are also catering to the industry demand for no-code tools. Some of them also provide no-code tools for computer vision, natural language processing, and other important AI technologies. To recapitulate, leveraging no-code platforms can solve accessibility, usability, speed, affordability, and scalability issues faced by organizations. These platforms enable workers at all levels to interact and contribute from a business standpoint, promising innovation from ‘scratch.’
