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Media jobs across the board — including those in advertising, technical writing, journalism, and any role that involves content creation — may be affected by ChatGPT and similar forms of AI, Madgavkar said. That’s because AI is able to read, write, and understand text-based data well, she added.

“Analyzing and interpreting vast amounts of language based data and information is a skill that you’d expect generative AI technologies to ramp up on,” Madgavkar said.

Economist Paul Krugman said in a New York Times op-ed that ChatGPT may be able to do tasks like reporting and writing “more efficiently than humans.”

Check out all the on-demand sessions from the Intelligent Security Summit here.

According to new reporting from the Financial Times, Google has invested $300 million in one of the most buzzy OpenAI rivals, Anthropic, whose recently-debuted generative AI model Claude is considered competitive with ChatGPT.

According to the reporting, Google will take a stake of around 10% and Anthropic will be required to use the money to buy computing resources from Google Cloud. The new funding will value the San Francisco-based company at around $5 billion.

Keep exploring at http://brilliant.org/ArtemKirsanov/
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My name is Artem, I’m a computational neuroscience student and researcher. In this video we will see why individual neurons essentially function like deep convolutional neural networks, equipped with insane information processing capabilities as well as some of the physiological mechanisms, that account for such computational complexity.

Patreon: https://www.patreon.com/artemkirsanov.
Twitter: https://twitter.com/ArtemKRSV

OUTLINE:
00:00 Introduction.
01:42 — Perceptrons.
03:43 — Electrical excitability and action potential.
07:12 — Cable theory: passive dendrites.
09:03 — Active dendritic properties.
12:10 — Human neurons as XOR gates.
19:11 — Single neurons as deep neural networks.
22:32 — Brilliant.
23:57 — Recap and outro.

REFERENCES (in no particular order):
1. Bicknell, B. A., Bicknell, B. A. & Häusser, M. A synaptic learning rule for exploiting nonlinear dendritic computation. Neuron (2021) doi:10.1016/j.neuron.2021.09.044.
2. Matthew Larkum. Are dendrites conceptually useful? Neuroscience (2022) doi:10.1016/j.neuroscience.2022.03.008.
3. Polsky, A., Mel, B. W. & Schiller, J. Computational subunits in thin dendrites of pyramidal cells. Nature Neuroscience 7621–627 (2004).
4. Tran-Van-Minh, A. et al. Contribution of sublinear and supralinear dendritic integration to neuronal computations. Frontiers in Cellular Neuroscience 9, 67–67 (2015).
5. Gidon, A. et al. Dendritic action potentials and computation in human layer 2/3 cortical neurons. Science 367, 83–87 (2020).
6. London, M. & Häusser, M. DENDRITIC COMPUTATION. Annu. Rev. Neurosci. 28503–532 (2005).
7. Branco, T., Clark, B. A. & Häusser, M. Dendritic Discrimination of Temporal Input Sequences in Cortical Neurons. Science 329, 1671–1675 (2010).
8. Stuart, G. J. & Spruston, N. Dendritic integration: 60 years of progress. Nat Neurosci 18, 1713–1721 (2015).
9. Smith, S. L., Smith, I. T., Branco, T. & Häusser, M. Dendritic spikes enhance stimulus selectivity in cortical neurons in vivo. Nature 503115–120 (2013).
10. Beniaguev, D., Segev, I. & London, M. Single cortical neurons as deep artificial neural networks. Neuron 109, (2021).
11. Michalikova, M., Remme, M. W. H., Schmitz, D., Schreiber, S. & Kempter, R. Spikelets in pyramidal neurons: generating mechanisms, distinguishing properties, and functional implications. Reviews in the Neurosciences 31101–119 (2019).
12. Larkum, M. E., Wu, J., Duverdin, S. A. & Gidon, A. The Guide to Dendritic Spikes of the Mammalian Cortex In Vitro and In Vivo. Neuroscience 489, 15–33 (2022).

CREDITS:

Robots are coming. And since the workers are already leaving the industry, no one will be harmed and service will be cheaper. Loving it!


Nearly three years since the coronavirus pandemic upended the labor market, restaurants, bars, hotels and casinos remain perpetually short-staffed. But these workers didn’t disappear, they found better jobs.

Welcome Back To Future Fuse Technology today is evolving at a rapid pace, enabling faster change and progress, causing an acceleration of the rate of change. However, it is not only technology trends and emerging technologies that are evolving, a lot more has changed this year due to the outbreak of COVID-19 making IT professionals realize that their role will not stay the same in the contactless world tomorrow. And an IT professional in 2023–24 will constantly be learning, unlearning, and relearning (out of necessity if not desire).Artificial intelligence will become more prevalent in 2023 with natural language processing and machine learning advancement. Artificial intelligence can better understand us and perform more complex tasks using this technology. It is estimated that 5G will revolutionize the way we live and work in the future. From the evolution of Artificial Intelligence (AI), the internet of things (IoT), and 5G network to cloud computing, big data, and analytics, technology has the capacity or potential to transform everything, revolutionizing the future of the world. Already, we see the rapid roll-out of autonomous vehicles (self-driving cars) currently in trial phases for all car companies, and Elon Musk’s Tesla is improving the technology by making it more secure and redefined. Forward-thinking and innovative companies seem not to miss any chance to bring breakthrough innovation to the world…in this video, we are looking into The World Will Be REVOLUTIONIZED by These 18 Rapidly Developing Technologies.

TAGS: #ai #technologygyan #futureTechnology.

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