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Cloud Computing


Preparing for quantum: next steps for enterprise

#artificialintelligence

Investment in quantum technologies will grow from US$412mn in 2020 to US$8.6bn by 2027, according to research firm IDC. Organisations that get started now will have a significant competitive advantage over those that continue to wait until quantum computing is a proven technology. Nevertheless, the complexity of quantum hardware and software development are forcing organisations to invest significantly in elite quantum expertise just to explore quantum-possible use cases for their potential business value. Gordon Davey is Cloud Services (Microsoft) General Manager at SoftwareONE, a leading global provider of end-to-end software and cloud technology solutions. Davey said: "Quantum technologies within enterprises are expected to take off over the next five years, with forecasts estimating that the market will eventually be worth anywhere between $500mn to $29bn, according to IBM. The development of quantum computing is speeding up, and technology firms are partnering up with businesses to work on bringing out the first commercial applications. A great example of this is Goldman Sachs, who recently assembled a'full team dedicated to quantum computing', and JP Morgan, who is now looking to implement the use of quantum computers as well. Additionally, Willis Tower Watson has also partnered up with Microsoft to develop the potential of quantum computing."


La veille de la cybersécurité

#artificialintelligence

The age of artificial intelligence (A.I.) is finally upon us. Consumer applications of A.I., in particular, have come a long way, leading to more accurate search results for online shoppers, allowing apps and websites to make more personalized recommendations, and enabling voice-activated digital assistants to better understand us. We all know there is tremendous potential value in data, which continues to grow exponentially. In fact, the world is creating 2.5 quintillion bytes of data every day (that's 2.5 followed by 18 zeros). To harness that potential, companies need A.I. to make sense of the data, and hybrid cloud computing platforms that can distribute it across organizations.


Computer Vision Pipeline with Kubernetes

#artificialintelligence

We produce a multitude of attributes (characteristics attached to an entity -- building, parcel, etc.) using various sources such as aerial imagery. The idea is to build Deep Learning models from a few thousand buildings using in-house-tagged labels or existing labels from open data. In a second step, the models are deployed on the whole French territory, which represents more than 35 million images to process (i.e. 4 TB of data to deal with). This second step is the focus of this post. The challenge is to be able to infer at low cost and in a short amount of time, (less than a day).


Skills and security continue to cloud the promise of cloud-native platforms

ZDNet

Joe McKendrick is an author and independent analyst who tracks the impact of information technology on management and markets. As an independent analyst, he has authored numerous research reports in partnership with Forbes Insights, IDC, and Unisphere Research, a division of Information Today, Inc. The KubeCon and CloudNativeCon events just wrapped up in Europe, and one thing has become clear: the opportunities are outpacing organizations' ability to leverage its potential advantages. Keith Townsend, who attended the conference, observed in a tweet that "talent and education is the number one challenge. I currently don't see a workable way to migrate thousands of apps without loads of resources. Information technology gets more complex every day, and there is no shortage of demand for monitoring and automation capabilities the build and manage systems. Cloud-native platforms are seen as remedies for not only improved maintenance, monitoring, and automation, but also for modernizing ...


Introducing the New Intelligent SAP Service Cloud

#artificialintelligence

We love it when people exceed expectations. Whether it's an athlete who steps up to replace an injured starter or a team that pulls together to deliver exceptional results, it is inspiring to see long-held assumptions about potential turned upside down. Now, service organizations have an opportunity to exceed traditional expectations in the same way. Instead of being considered simply a means of connection and cost containment post-customer purchase, intelligent service teams can become a strategic driver to direct value back to the business. Focusing on speed, insights, and accuracy, SAP Service Cloud resolves customer issues at unmatched speed -- protecting the brands promise and securing future growth.


D2iQ Streamlines Smart Cloud-Native Application Deployments with Kaptain AI/ML 2.0

#artificialintelligence

D2iQ, the leading enterprise Kubernetes provider for smart cloud-native applications, announced version 2.0 of Kaptain AI/ML, the enterprise-ready distribution of open-source Kubeflow that enables organizations to develop, deploy, and run artificial intelligence (AI) and machine learning (ML) workloads in production environments. Powered by Kubeflow 1.5, the Kubernetes machine learning toolkit, Kaptain AI/ML now provides data science teams with features such as expanded control for mounting data volumes and increased visibility into idle notebooks, so they can spend more time developing and less time managing infrastructure. The enhanced user experience enables data scientists to more effectively manage the lifecycle of AI and ML models without the need for infrastructure knowledge and skill sets. By simplifying the deployment and full lifecycle management of AI and ML workloads at scale, Kaptain AI/ML 2.0 accelerates the impact of smart cloud-native applications. This enables organizations to drive better business results by more quickly delivering new smart products and services, becoming more agile when updating models, and driving smarter customer experiences.


Google unveils the world's largest publicly available machine learning hub

#artificialintelligence

Google I/O 2022, Google's largest developer conference, kicked off with a keynote speech from Alphabet CEO Sundar Pichai. The keynote speech had major announcements including the launch of Pixel watch, updates on PaLM and LaMDA, advancements in AR and immersive technology etc. Let us look at the key highlights. "Recently we announced plans to invest USD 9.5 billion in data centers and offices across the US. One of our state-of-the-art data centers is in Mayes County, Oklahoma. I'm excited to announce that, there, we are launching the world's largest, publicly-available machine learning hub for our Google Cloud customers," Sundar Pichai said.


What to expect from Google I/O 2022

#artificialintelligence

Google I/O 2022, the most awaited developers' conference of the year, is around the corner. With more than 200 speakers, the summit will cover a broad spectrum of topics and will have a slew of announcements on the latest innovations in AI and ML. The I/O adventure also makes a comeback this year: Users can explore the platform to see product demos, chat with Googlers, earn Google Developer profile badges and virtual swag, engage with the developer community, create an avatar, and look for easter eggs. Seek out your next Adventure at Google I/O 2022! The conference is scheduled to start at 10:30 pm IST on May 11, 2022, and will kick off with Alphabet CEO Sundar Pichai's keynote speech.


How I became an ML hackathon Grandmaster

#artificialintelligence

HSBC's Akash Gupta has won over 45 machine learning hackathons to date. The MachineHack Grandmaster has come second thrice in a row and is currently ranked sixth on the platform. "I've always been fascinated by numbers and patterns. I got very curious about algorithms – how they are made, how they work, and what we can do with them– after I took Andrew Ng's machine learning course," said Akash Gupta. The data scientist spoke about his MachineHack journey in an exclusive interview with Analytics India Magazine.


You are Not Using the Right AI/ML API: Here's Why

#artificialintelligence

Eden AI simplifies the use and deployment of AI technologies by providing a unique API connected to the best AI engines. Companies are increasingly using Artificial Intelligence services, especially when it comes to automating internal processes or improving their customers' experience. The strong development of AI makes it a commodity. These functionalities can be used in several fields: health, human resources, tech, etc. The big players in the cloud market (Amazon Web Services, Microsoft Azure or Google Cloud) offer solutions that provide access to this type of service, but there are also smaller providers that are already competing with them: Mindee, Dataleon, Deepgram, AssemblyAI, Rev.AI, Speechmatics, Lettria, etc.