Collaborating Authors


What to expect from Google I/O 2022


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.

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


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.

Best Predictive Analytics Tools and Software 2022


Managing data has always been a challenge for businesses. With new sources and higher volumes of data coming in all the time, it's more important than ever to have the right tools in place. Predictive analytics tools and software are the best way to accomplish this task. Data scientists and business leaders must be able to organize data and clean it to get the process started. The next step is analyzing it and sharing the results with colleagues.

The Hyperscalers Point The Way To Integrated AI Stacks


Enterprises know they want to do machine learning, but they also know they can't afford to think too long or too hard about it. They need to act, and they have specific business problems that they want to solve. And they know instinctively and anecdotally from the experience of the hyperscalers and the HPC centers of the world that machine learning techniques can be utterly transformative in augmenting existing applications, replacing hand-coded applications, or creating whole new classes of applications that were not possible before. They also have to decide if they want to run their AI workloads on-premise or on any one of a number of clouds where a lot of the software for creating models and training them are available as a service. And let's acknowledge that a lot of those models were created by the public cloud giants for internal workloads long before they were peddled as a service.

Machine Learning on Google Cloud (Vertex AI & AI Platform)


Are you a data scientist or AI practitioner who wants to understand cloud platforms? Are you a data scientist or AI practitioner who has worked on Azure or AWS and curious to know how ML activities can be done on GCP? If yes, this course is for you. This course will help you to understand the concepts of the cloud. In the interest of the wider audience, this course is designed for both beginners and advanced AI practitioners.

The real cost of cloud computing - VentureBeat - UrIoTNews


We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 – 28. The public cloud is growing rapidly and the market for the technology is expected to reach $1.3 trillion by 2025. The cloud has revolutionized the computing industry and enabled many applications, business models and enterprises, which otherwise wouldn't have been possible. Immediate availability, scalability, minimal capital expenditure and streamlined developer experience are its main advantages -- but it comes at a cost. Due to a lack of in-house infrastructure optimization capabilities, most enterprises stick to the cloud even after achieving certain maturity. To keep cloud spending under control, enterprises have built or acquired tools and services.

Top 3 Digital Transformation Strategies of 2022


The past two years of the pandemic have been marked by a period of rapid technological change. Amidst supply chain disruptions and changes in consumer behaviours, organisations have turned to digital transformation strategies to stay agile and resilient. The COVID-19 crisis has made it clear that technology is the lynchpin of organisational resilience and agility. As the pandemic disrupted global supply chains, forced employees to work from home and triggered a massive shift of consumer behaviour to online channels, digital technologies have played a pivotal role in keeping organisations afloat. According to Google's State of the API Economy 2021, digital transformation was the leading business imperative of 2020, based on a survey of 700 IT decision-makers from around the world.

Cloud computing has all the momentum, but we still live in an on-premises world for now


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. With all the analyst, press and conference talk about the ascendency of cloud, one can be forgiven for assuming that the entire world is now running on AWS, Azure or Google Cloud and other providers. However, at this stage, only seven percent of enterprises are truly all-cloud. This number is likely to more than double over the next two years, but still represents the minority of enterprises.

Federated Learning


Then, we will start by loading the dataset on the devices in IID, non-IID, and non-IID and unbalanced settings followed by a quick tutorial on PySyft to show you how to send and receive the models and the datasets between the clients and the server. This course will teach you Federated Learning (FL) by looking at the original papers' techniques and algorithms then implement them line by line. In particular, we will implement FedAvg, FedSGD, FedProx, and FedDANE. You will learn about Differential Privacy (DP) and how to add it to FL, then we will implement FedAvg using DP. In this course, you will learn how to implement FL techniques locally and on the cloud. For the cloud setting, we will use Google Cloud Platform to create and configure all the instances that we will use in our experiments. By the end of this course, you will be able to implement different FL techniques and even build your own optimizer and technique. You will be able to run your experiments locally and on the cloud.

AWS sharpens focus on modern data strategies with an array of new products


To further strengthen our commitment to providing industry-leading coverage of data technology, VentureBeat is excited to welcome Andrew Brust and Tony Baer as regular contributors. Amazon Web Services (AWS) is on a mission to enable organizations -- including startups, enterprises and government agencies -- to become more agile and innovate faster at lower costs. Last year, an AWS executive told VentureBeat that a priority for AWS in 2022 will be automation at scale, allowing customers to bolster the security of their cloud environments. To advance its mission, AWS today unveiled innovations across several services, including databases, machine learning, IoT and application development. The announcement came yesterday at the AWS Summit, San Francisco, where Swami Sivasubramanian, VP of data, analytics and ML services at AWS, offered details on the new product offerings in a keynote address.