How much can we afford to forget, if we train machines to remember? - Gene Tracy | Aeon Ideas
Our ancestors had a manual 'peer-to-peer' memory network to pass on knowledge to the future generations; it wasn't reliable but worked for a long time.
Now we believe AI is better and more objective to provide us with information, which might not be the case.
This is a professional note extracted from an online article.
Read more efficiently
Save what inspires you
IDEA EXTRACTED FROM:
As machines become increasingly capable, along with computer memory, power and space being abundantly available, our brains are in a transition phase.
Earlier we had to remember a lot, do calculations on paper, and jog our memories to recall something. More and more of such information isn't processed by our brains anymore and is taken care of by machines.
As technology advances and the internet gets dramatically more powerful, the need to retain information in our heads diminishes.
Google and other search engines which deploy AI, work as our 'memory partners' and provide us access to most of the human knowledge.
We may be on to a hybrid platform, an extension of our minds, where neural implants and accelerated access to knowledge can blur the lines between what is inside our mind and in an AI machine.
This fusion of Artificial Intelligence enabled devices and our brains might be the future of information and communication.
SIMILAR ARTICLES & IDEAS:
Future-proofing your career to stay relevant isn't about learning how to code or going back to college.
It is about having a career plan with a long-term vision, taking into account the current job-market conditions, economic factors, emerging opportunities, personal interests, and family realities.
A life cycle of a job is shrinking rapidly, and if you're not re-inventing yourself or pivoting on time, you are rendered out of work sooner than in the past decades.
We need to check our career plan and ask ourselves what skills need to be developed to pursue future opportunities, in this shifting economy.
4 more ideas
Neuroevolution is a form of artificial intelligence. It is a meta-algorithm, an algorithm for designing algorithms. It adopts the principles of biological evolution in order to design smarter algor...
Traditionally, evolutionary algorithms are used to solve specific problems. For instance, the ability to control a two-legged robot. Solutions that perform the best on some metrics are selected to produce offspring.
In spite of successes, these algorithms are more computationally intensive than approaches such as "deep learning."
It goes beyond traditional evolutionary approaches. It explains innovation. Instead of optimizing for a specific goal, it embraces the creative exploration of a diverse population of solutions.
The steppingstone’s potential can be seen by analogy with biological evolution: feathers likely evolved for insulation and only later became handy for flight.
4 more ideas
Before the Industrial revolution, everyone worked out of their home and sold their goods from there. With the Industrial Revolution came the need for automation and factories, and employ...
Just after WW2, there was a rise in corporate headquarters and larger office spaces and cubicles. During this time, the 8-hour workday was established.
Then came the advancements in computers and technology that lead to remote workers of today. The internet and public WiFi allowed employees to do everything they would in their cubicle, but outside the office. They can also work all hours of the day.
4.3 million people currently work from home in the United States at least half of the time, and this figure has grown by 150% in the last 13 years.
Remote workers tend to have higher engagement rates and higher productivity levels. Once they switch to remote work, they rarely want to become office bound again.
2 more ideas