Artificial general intelligence: Key insights and future

There is no doubt that the emergence of powerful technologies tends to have significant spatial ramifications for nations. This is particularly true of digital technologies, where innovation tends to be concentrated but products are widely used, given network effects across massive platforms. “AI is increasingly defined by the actions of a small set of private sector actors, rather than a broader range of societal actors,” observed Stanford University’s Institute for Human-Centered Artificial Intelligence in a report earlier this year. They are also likely to ensure that most AI development activity (and hiring) remains highly concentrated in a short list of “superstar” metro areas and early adopter hubs, as Brookings described in a 2021 report. In that report, Brookings documented the technical and business dominance of early-stage AI development centers such as San Francisco, San Jose, Calif., Seattle, and Boston. Fintech-enabled marketplaces will have an advantage in that they’ll be able to capture more of the transaction value quickly by simultaneously selling more complementary goods or services to the same consumer.

Himel and Seamans (2017) discuss how policymakers might address these issues and describe several policy solutions to consider, including provisions that would institute temporary data monopolies, data portability regimes, and the use of trusted third parties. A key feature of all these suggestions is that incumbents’ monopoly access to operational data would be somewhat limited. This helps you gradually learn about generative AI while minimizing potential disruptions. Your focus should be on creating an environment that encourages quick experimentation and innovation.

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Growth of these fit-for-purpose FMs will be driven by a backlash to the huge expense of running large models such as GPT. When it comes to LLMs, the meek (in the form of smaller language models) will inherit the Earth. With the learning curve, data scientists will grow more prescient at optimizing right-sized training data corpuses for generative models. Artificial Intelligence in enterprise solutions stands out from traditional software systems because of the exponential speed at which one can do things. In today’s hyper-connected world, where speed of processing and speed to market are critically important factors, enterprise AI has the potential to accelerate digital transformation.

By monetizing well as growing audience, the online dating industry could be a good match for investors. A revolutionary approach could replace traditional cancer treatments and create new revenue opportunities for makers and investors. The finance industry has embraced generative AI and is extensively harnessing its power as an invaluable tool for its operations. Stay on top of the latest AI governance news, learn about our new offerings and engage in the development of the AI governance profession.

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Similarly, Congress should fully fund other shortchanged features of the CHIPS and Science Act, such as ones to build the STEM workforce through scholarships, fellowships, and traineeships. Finally, as in the case of cluster development, the nation needs to better support regional efforts to train the diverse AI workforces they will need to carve out viable spots on the emerging AI map. For this, Congress should make large-scale, flexible challenge grants such as the EDA’s Good Jobs Challenge permanent.

GenAI tools can therefore be used to do the brilliant work of performing knowledge-intensive tasks that are critical to driving top-line business growth and innovation. Moreover, they can help synthesize and make sense of a vast world of knowledge beyond the capabilities of any ordinary human being. Responding to attacks in a timely and efficient manner with the same level of intelligence as human operators could be transformative while also freeing up valuable IT resources. Moreover, generative AI models could likely be effective in formulating scenarios in which enterprise systems could be deemed vulnerable, boosting proactive defenses. We believe this is an area where existing cloud deployed cybersecurity vendors are in an ideal position to innovate and deliver, given the data and talent they have access too. Vertical specific industry solution providers may also be in an ideal position to access valuable data and deliver differentiated add-on AI-led services.

Read more about The Economic Potential of Generative Next Frontier For Business Innovation here.