List of the top 20 machine learning, artificial intelligence, AI Startups to watch In 2021.
Read MoreThe Top 20 Machine Learning Startups To Watch In 2021
Category: Business
Survey finds 96% of execs are adopting ‘offensive AI’ against cyberattacks
“Offensive AI” will enable cybercriminals to direct attacks on enterprises while flying under the radar of conventional, rules-based detection tools. That’s according a new survey published by MIT Technology Review Insights and Darktrace, which found that more than half of business leaders believe security strategies based on human-led responses are failing.
Read MoreWhat is the Data Science Strategy of Microsoft?
The days when siloed, monolithic data stores were the rule is long gone, and those that are still standing are insufficient for business needs in today’s digital world. As part of its digital transformation, Microsoft is modernizing the data estate to unleash the power of Artificial Intelligence.
Read MoreArtificial Intelligence in Manufacturing: Time to scale and time to accuracy
Asset-intensive organizations are pursuing digital transformation to attain operational excellence, improve KPIs, and solve concrete issues in the production and supporting process areas. AI-based prediction models are particularly useful tools that can be deployed in complex production environments.
Read MoreDelivering AI/ML without proper Dataops is just wishful thinking!
Given the iterative nature of AI/ML projects, having an agile process of building fast and reliable data pipelines (referred to as DataOps) has been the key differentiator in the ML projects that succeeded (unless there was a very exhaustive feature store available which is typically never the case).
Read MoreWhy you should use Continuous Integration and Continuous Deployment in your Machine Learning projects
Continuous integration (CI), continuous delivery (CD) and continuous testing (CT) are at the core of Machine Learning Operation (MLOps) principles. If you’re a data scientist or machine learning engineer or an IT business leader investing in data science teams, and willing to extend their ML capabilities. MLOps might be the next step that delivers significant value to your business, speeding up development and implementation phases for any machine learning project.
Read MoreReverse Logistics Company uses AI to find Value in Retail
While “Retail Apocalypse” would no doubt make a great sequel to the iconic movie “Apocalypse Now”. While most fingers point at Amazon (AMZN) as the primary culprit behind the destruction of the American strip mall Main Street America, the retail apocalypse is another example of evolve or die. Margins are tight, so companies looking to survive are searching for ways to eke out value anywhere along the supply chain. One emerging avenue is through something called reverse logistics.
Read MoreDo companies need a Chief AI-Ethics Officer?
The world we live in is becoming more and more data-driven. This is causing companies to make more and more use of AI techniques such as machine learning and deep learning. The task of the Chief AI Ethics Officer (CAIEO) should not be primarily technical. Instead, it should sensitize data scientists, machine learning engineers, and developers to ethical issues. The whole process should be firmly integrated into the respective process models and phases.
Read MoreFollow the Money March 2021: 15 funded Machine Learning companies
March 2021 latest funding covering artificial intelligence, machine learning, robotics, and innovation.
Read MoreArtificial Intelligence is playing a big role in Fraud Investigation
New and complex challenges behind managing the fraud investigation are a strenuous task in itself. Well, it doesn’t end there. Cross-border probe adds to the already existing complexity. Such an investigation could highlight bribery, corruption, data breach, conflict of interest, fraud in financial reporting and IP theft, to name a few.
Read More5 common ways companies use RPA to enhance Document Processing
With all the hype around robotic process automation (RPA), it can be helpful to remember that the vast majority of the data running through RPA automations originates or terminates with a document. In fact, I’d estimate that about 80% of RPA automations fall into this category.
Read MoreOpenAI is open for business, GPT-3 powers the Next generation of Apps
OpenAI’s GPT-3 is well known in the machine learning world for their human like writing, where it is powering 300 applications, supporting GPT-3–powered search, conversation, text completion, and other advanced AI features through their API. As reference, here is a shortlist of example OpenAI’s use cases in how developers and applications are using GPT-3.
Read MoreOptimizing Machine Learning: MLOps and its significant benefits
MLOps ensures effective lifecycle management of ML models. Machine learning operations (MLOps) is a procedure that has recently entered the dictionary of technology organizations. More or less, MLOps is a method of optimizing the work process of data science and machine learning teams. It’s like DevOps from numerous points of view, additionally focusing on automation, continuous processes for testing and delivery, and collaboration between teams.
Read MoreLanguage AI startup Moveworks expands beyond IT to finance, HR, other corporate communications
Language AI startup Moveworks argues its use of natural language understanding machine learning is broadly applicable to many corporate functions that have a support component such as HR and legal affairs.
Read MoreKey NoOps insights from DevOps Leaders
NoOps is coming, in some form or another. Whether you have homegrown DevOps or outsourced DevOps, it’s time to realize that a simpler way is coming: NoOps automation. We spoke with a group of IT pros to get their perspective and insights, including James Rutt, CIO, The Dana Foundation; Rahul Subramaniam, CEO, DevFactory; and Mark Hahn, director of DevOps and cloud strategies, Ciber Global.
Read More[Case Study] MLOps at GreenSteam: Shipping Machine Learning
GreenSteam is a company that provides software solutions for the marine industry that help reduce fuel usage. Excess fuel usage is both costly and bad for the environment, and vessel operators are obliged to get more green by the International Marine Organization and reduce the CO2 emissions by 50 percent by 2050.
Read MoreTop AI companies in the World creating massive Disruption
Artificial intelligence is invading each industry, permitting vehicles to drive without drivers, helping doctors with clinical diagnoses, and imitating the manner in which humans talk. Yet, for every one of the legitimate and exciting ways, it’s changing the tasks computers can play out, there’s a lot of hype, as well. As artificial intelligence has become a strong power in business, today’s top AI companies in the world are leaders of this growing technology.
Read MoreBenefits that companies are getting from AI/ML
Artificial Intelligence and Machine Learning have become the centerpiece of strategic decision-making for organizations. They are disrupting the way industries and roles function — from sales and marketing to finance and HR, companies are betting big on AI and ML to give them a competitive edge.
Read MoreArtificial Intelligence in the Logistics Market: an analysis of the State of the Art
Artificial Intelligence is set to reshape Logistics. But how does the current scenario look like? Here is our analysis on current dynamics, interesting synergies and future trends.
Read MoreWhat are the market drivers, restraints and opportunities of AI?
Companies across the world are increasingly turning to Artificial Intelligence implementation for their smooth business operations. The technology has become very constructive in performing a wide range of tasks that are complex and cumbersome for humans, bolstering employee productivity. The use of AI can also aid enterprises to combat cybersecurity risks and thwart them from potential data breaches. With the growing capabilities of AI across diverse business functions, here are the key driver, restraints and opportunities AI presents.
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