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From now on, the generational divide within the workplace looks set to revolve around remembering the days before AI dominated almost every aspect of our work lives, and the period after.
In fact, according to a recent study by McKinsey, generative AI is now being used by 79% of all workers and 22% use it regularly to complete their everyday work tasks.
Couple this with the fact that AI is predicted to eliminate 83 million global jobs by 2027 and it’s easy to see why for those starting out in their careers, AI will not only shape their day-to-day but have a massive impact on their overall career trajectory.
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This is probably why educational institutions are the second largest cohort to utilize ChatGPT within the workplace after tech, and colleges are racing to build state-of-the-art AI faculties to not only facilitate student demand but address the skills gap which has seen 75% of companies struggle to recruit qualified talent.
At the University of Albany, 27 new faculty members specializing in artificial intelligence have been hired “to incorporate elements of AI teaching and research across all academic programs.”
Elsewhere, the University of Southern California has invested more than $1 billion in its AI initiative which included courses in advanced computation, quantum computing, AI and ethics.
And Purdue University has established its Institute for Physical AI (IPAI), the first of its kind in the U.S., which will focus on areas including robotics, deep fake detection and AI-based manufacturing among others.
So, what does this mean for those who fall into the “days before AI” camp?
According to the World Economic Forum (WEF), 50% of all employees will need reskilling by 2025 as the adoption of technology increases.
And while keeping hard skills fresh and up-to-date is imperative, there’s also been a renewed focus on the importance of soft skills.
As such, the WEF has also identified the top 10 skills of tomorrow and critical thinking and problem-solving top the list along with creativity, leadership, resilience, flexibility and stress tolerance — all of which machines are yet to master.
Whatever stage you’re at in your working life, the VentureBeat Job Board is the perfect place to start your search if you’re looking for a way to futureproof your career prospects. It features thousands of jobs in companies that are actively hiring, like the three below.
NVIDIA is seeking a Senior Deep Learning Algorithms Software Engineer to join its deep learning algorithms team to develop and commercialize AI solutions related to natural language processing, computer vision, speech, text and recommendation systems. Day-to-day you’ll be developing algorithms for deep learning, data analytics, machine learning or scientific computing, constructing and curating large problem specific datasets, analyzing and improving the performance of graphic processing unit implementations and publishing state-of-the-art results on Github and scientific publications. View more details here.
Software Engineer Lead, Java — Springboot, Capgemini, Atlanta
Capgemini Engineering is an integral part of the Capgemini Group which addresses business needs, from strategy and design to operations, fuelled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms. As Software Engineer Lead, you will design, develop and unit test APIs and applications, collaborate with multi-functional teams (such as architects, testers, product managers) and deliver, contribute to design architectural discussions, help triage, identify root cause for issues and implement solutions and document high and low level designs, sequence diagrams and flow diagrams etc. See the full job description here.
Project Starline from Google combines advances in hardware and software to enable friends, families and co-workers to feel together, even when they’re cities (or countries) apart. In this Senior Product Manager role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development. You’ll need a Bachelor’s degree or equivalent practical experience, eight years’ of experience in product management, consulting, co-founder or related technical role, and three years’ of experience in building and shipping technical products. Get more information here.
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