Elon Musk made some striking predictions about the impact of artificial intelligence (AI) on jobs and income at the inaugural AI Safety Summit in the U.K. in November.
The serial entrepreneur and CEO painted a utopian vision where AI renders traditional employment obsolete but provides an “age of abundance” through a system of “universal high income.”
“It’s hard to say exactly what that moment is, but there will come a point where no job is needed,” Musk told U.K. Prime Minister Rishi Sunak. “You can have a job if you want to have a job or sort of personal satisfaction, but the AI will be able to do everything.”
Explores how jobs and skills will evolve over the next five years. This fourth edition of the series continues the analysis of employer expectations to provide new insights on how socio-economic and technology trends will shape the workplace of the future.
Devin, SIMA, Figure 1, all in 24 hours. What does it mean and are AI models taking the wheel? I’ll go through 5 relevant papers and 11 articles to get you all the relevant details, from what exactly Devin accomplished, and didn’t, to DeepMind’s new AGI-attempt-in-3D (SIMA) to just how far AI agents have come and what that means for the future of jobs. They’ll also be a guest star … discussing … me?
AI Insiders [Exclusive videos, Discord, Interviews and More]: / aiexplained.
There is a new AI tool so smart that it can write code, create websites, and software with just a single prompt. Devin, created by the tech company Cognition, is the first AI software engineer. It can do pretty much everything you ask it to do. And the AI tool does not come with the intention to replace human engineers, it is designed to work hand-in-hand with them. The makers say that the AI tool has not been launched to replace human engineers but to make their lives easier.
“Today we’re excited to introduce Devin, the first AI software engineer. Devin is the new state-of-the-art on the SWE-Bench coding benchmark, has successfully passed practical engineering interviews from leading AI companies, and has even completed real jobs on Upwork. Devin is an autonomous agent that solves engineering tasks through the use of its own shell, code editor, and web browser,” Cognition posted on Twitter aka X.
What makes Devin stand out is its incredible ability to think ahead and plan complex tasks. It can make thousands of decisions, learn from its mistakes, and get better over time. Plus, it has all the tools a human engineer needs, like a code editor and browser, right at its digital fingertips. Devin is considered the most advanced or cutting-edge solution available for evaluating software engineering tasks based on the SWE-bench coding benchmark. Essentially, it performed exceptionally well compared to other solutions when tested against a standard set of software engineering problems. The AI tool performed well in practical engineering interviews conducted by top artificial intelligence companies. These interviews likely involved tasks and challenges relevant to the field of AI and software engineering, and the AI assistant managed to meet expectations.
AI startup company Figure, which emerged from stealth last year, has unveiled the latest upgrades to its Figure 1 humanoid robot.
Founded in 2022 and publicly announced in March 2023, Figure is a California-based company with 80 employees that is building autonomous, general‑purpose humanoid robots. Its aim is to address labour shortages, fill jobs that are undesirable or unsafe for humans, and support a supply chain on a global scale.
The company is backed by a number of tech leaders including Amazon founder Jeff Bezos, chipmaker NVIDIA, and Microsoft, and it recently announced a deal with ChatGPT‑maker OpenAI. Figure’s latest round of funding – which closed at $675 million – brought its total valuation to an impressive $2.6 billion.
A new generative artificial intelligence startup called Cognition AI Inc. is looking to disrupt coding with the launch of a new tool that can autonomously create code for entire engineering jobs, including its own AI models.
That tool’s name is Devin, and it takes the premise of GitHub Inc.’s and Microsoft Corp.’s Copilot developer tool much further, as it can carry out entire jobs on its own, rather than simply assist a human coder.
In a video (below) attached to a blog post announcing Devin, Cognition Chief Executive Scott Wu demonstrates how users can view the model in action. They can see its command line, code editor and workflow as it goes step-by-step, completing comprehensive coding projects and data research tasks assigned to it.
Artificial Intelligence (AI) and Deep Learning, with a focus on Natural Language Processing (NLP), have seen substantial changes in the last few years. The area has advanced quickly in both theoretical development and practical applications, from the early days of Recurrent Neural Networks (RNNs) to the current dominance of Transformer models.
Models that are capable of processing and producing natural language with efficiency have advanced significantly as a result of research and development in the field of neural networks, particularly with regard to managing sequences. RNN’s innate ability to process sequential data makes them well-suited for tasks involving sequences, such as time-series data, text, and speech. Though RNNs are ideally suited for these kinds of jobs, there are still problems with scalability and training complexity, particularly with lengthy sequences.
When will AI match and surpass human capability? In short, when will we have AGI, or artificial general intelligence… the kind of intelligence that should teach itself and grow itself to vastly larger intellect than an individual human?
According to Ben Goertzel, CEO of SingularityNet, that time is very close: only 3 to 8 years away. In this TechFirst, I chat with Ben as we approach the Beneficial AGI conference in Panama City, Panama.
We discuss the diverse possibilities of human and post-human existence, from cyborg enhancements to digital mind uploads, and the varying timelines for when we might achieve AGI. We talk about the role of current AI technologies, like LLMs, and how they fit into the path towards AGI, highlighting the importance of combining multiple AI methods to mirror human intelligence complexity.
We also explore the societal and ethical implications of AGI development, including job obsolescence, data privacy, and the potential geopolitical ramifications, emphasizing the critical period of transition towards a post-singularity world where AI could significantly improve human life. Finally, we talk about ownership and decentralization of AI, comparing it to the internet’s evolution, and envisages the role of humans in a world where AI surpasses human intelligence.
Like Gates, Leslie doesn’t dismiss doomer scenarios outright. “Bad actors can take advantage of these technologies and cause catastrophic harms,” he says. “You don’t need to buy into superintelligence, apocalyptic robots, or AGI speculation to understand that.”
“But I agree that our immediate concerns should be in addressing the existing risks that derive from the rapid commercialization of generative AI,” says Leslie. “It serves a positive purpose to sort of zoom our lens in and say, ‘Okay, well, what are the immediate concerns?’”
In his post, Gates notes that AI is already a threat in many fundamental areas of society, from elections to education to employment. Of course, such concerns aren’t news. What Gates wants to tell us is that although these threats are serious, we’ve got this: “The best reason to believe that we can manage the risks is that we have done it before.”
