Artificial intelligence is about to change lead generation and conversion as you know it. In the process, it'll have a transformative impact on companies and careers. AI is a blanket term that covers several different technologies. You might have heard of some of them, like machine learning, computer vision, and natural language processing. Even if you don't know much about it, though, you probably use AI-powered technology dozens or hundreds of times per day.
Undoubtedly, artificial intelligence (AI) is able to support organisations in tackling their threat landscape and the widening of vulnerabilities as criminals have become more sophisticated. However, AI is no silver bullet when it comes to protecting assets and organisations should be thinking about cyber augmentation, rather than just the automation of cyber security alone. Areas where AI can currently be deployed include the training of a system to identify even the smallest behaviours of ransomware and malware attacks before it enters the system and then isolate them from that system. Other examples include automated phishing and data theft detection which are extremely helpful as they involve a real-time response. Context-aware behavioural analytics are also interesting, offering the possibility to immediately spot a change in user behaviour which could signal an attack.
Virtual assistants turn 16 this year and you don't have to look too hard – or speak too loudly – to find them. In fact, there will be around 8 billion voice-based devices by 2023 – more than the world's population today. From Amazon's Echo and Google's Assistant to Apple's Siri, Samsung's Bixby and Microsoft's Cortana, billions of people around the world are using their voices every day to schedule appointments, get directions, play music or get answers quickly-- all things that once required us to tediously type or write. Even Twitter recently announced that users can now audio tweet their inner musings. And yet, despite widespread adoption of voice-based devices in our personal lives, applications based on voice are nowhere as pervasive in our professional lives as they are in our homes.
In a letter to congress sent on June 8th, IBM's CEO Arvind Krishna made a bold statement regarding the company's policy toward facial recognition. "IBM no longer offers general purpose IBM facial recognition or analysis software," says Krishna. "IBM firmly opposes and will not condone uses of any technology, including facial recognition technology offered by other vendors, for mass surveillance, racial profiling, violations of basic human rights and freedoms, or any purpose which is not consistent with our values and Principles of Trust and Transparency." The company has halted all facial recognition development and disapproves or any technology that could lead to racial profiling. The ethics of face recognition technology have been in question for years. However, there has been little to no movement in the enactment of official laws barring the technology.
Smart & Final is rolling out Hypersonix's AI-driven analytics platform to support the company's enterprise analytics and digital transformation initiatives. The two companies started working together sixty days ago on a successful pilot program. With this announcement, Smart & Final officially joins a handful of early adopters in the grocery and consumer-commerce industries turning to the innovative company to help navigate the post-COVID-19 market. "Hypersonix is a key ingredient in leveraging actionable analytics that can be operationalized by our business teams as part of our on-going digital transformation," said Ed Wong, EVP and Chief Digital Officer at Smart & Final. "We established a great innovation-centric collaboration with Hypersonix where we are finding new ways to address our needs in key strategic areas for our business."
As many parts of the world continue to remain in lockdown due to the global pandemic, many countries have started to ease the restrictions. Particularly in Australia & New Zealand, schools have reopened, workers are heading back to their offices, and restaurants & retail stores are beginning to resume trade with new set of guidelines. These guidelines might also vary from one state to another and hence businesses that operate and have offices in different states, need to provide relevant updates to their employees to be able to comply with the new regulations. The most common practice from employers is to send out regular emails outlining the guidelines. Chatbots are beginning to play a vital role in providing real-time upto date information.
Computer vision summit CVPR has just (virtually) taken place, and like other CV-focused conferences, there are quite a few interesting papers. More than I could possibly write up individually, in fact, so I've collected the most promising ones from major companies here. Facebook, Google, Amazon and Microsoft all shared papers at the conference -- and others too, I'm sure -- but I'm sticking to the big hitters for this column. Redmond has the most interesting papers this year, in my opinion, because they cover several nonobvious real-life needs. One is documenting that shoebox we or perhaps our parents filled with old 3x5s and other film photos.
In our last post on deploying a machine learning pipeline in the cloud, we demonstrated how to develop a machine learning pipeline in PyCaret, containerize it with Docker and serve it as a web application using Google Kubernetes Engine. If you haven't heard about PyCaret before, please read this announcement to learn more. In this tutorial, we will use the same machine learning pipeline and Flask app that we built and deployed previously. This time we will demonstrate how to containerize and deploy a machine learning pipeline serverless using AWS Fargate. This tutorial will cover the entire workflow starting from building a docker image locally, uploading it onto Amazon Elastic Container Registry, creating a cluster and then defining and executing task using AWS-managed infrastructure i.e.
LinkedIn has been at the cutting edge of AI for years and uses AI in many ways users may not be aware of. I recently had the opportunity to talk to Igor Perisic, Chief Data Officer (CDO) and VP of Engineering at LinkedIn to learn more about the evolution of AI at LinkedIn, how it's being applied to daily activities, how worldwide data regulations impact the company, and some unique insight into the changing AI-related work landscape and job roles. Very early on at LinkedIn, data was identified as one of the company's core differentiating factors. Another differentiating factor was a core company value of "members first" (clarity, consistency, and control of how member data is used) and their vision to create economic opportunity for every member of the global workforce. As LinkedIn began finding more and more ways to weave AI into their products and services, they also recognized the importance of ensuring all employees were well-equipped to work with AI as needed in their jobs.
Icertis, the leading provider of enterprise contract management in the cloud, today announced Betsy Atkins, a three-time CEO, serial entrepreneur and founder of Baja Corporation, has joined its Board of Advisors. Having co-founded successful tech companies and having served on a wide variety of corporate boards, Betsy brings a wealth of expertise in leading companies through rapid expansion. As a key adviser, Betsy will provide strategic counsel on corporate governance, risk management, and scaling Icertis' global leadership in the rapidly growth Contract Lifecycle Management (CLM) market. The addition of Betsy to the Board of Advisors comes at a pivotal time as Icertis continues to grow rapidly and add iconic brands as customers. In 2019, the company's subscription revenues grew close to 100% YoY and, today, the company maintains the world's largest portfolio of contracts, over 7.5 million, with a total contracted value of over $1 trillion for the world's leading companies.