Space Analoology: Airport now or waiting?
Recently, I have learned about the exciting examination of astronomers, in my opinion, completely illustrates the problem of business reading today.
Consider this scenario: The year after 2100, astronomers have found a planet in the Alpha Centauri (just 4,4 bright 4,4) life. Mankind decides to send a trip there. Current technology allows us to build a ship for 200 years to reach, walking 2.2% of the speed of light. For a long time, but it is possible.
However, technology is not standing. Scientists predict that in 20 years, advanced engines will appear, reduce the trip from 15 to 150 years. Should you introduce a trip now, great investment services, if the waiting can do it immediately and better?
What if, in 50-70 years, technology improves the 100th anniversary of 100 years? Or, on the other hand, does progress decrease, and wait and turn into vain?
Potential strategies:
- Expect a perfect moment – but when will you arrive?
- Send a ship after all success – but that is very expensive.
- Send a single ship now and don’t avenge – but we may have missed something important?
The problem is very similar to that deal with corporate literacy today: Use AI now or wait?
Firm and AI reading: The same problem
Today, artificial intelligence changes education. Generative Models (ChatGPT, Gemini, Claude) has already written training equipment, create exams, and sync the content of the labor requirements. But technology is advanced:
- The power to charge are more than the law (Moore law, although slowly, is still holding).
- The language models are violent. GPT-4 is already better than GPT-3, so what will happen annually?
- Stuff-made tools come quickly. Newly required months are now being made in a few hours.
If we use AI now, we can earn more than competitors. But there is a risk that in a year or two, the highest quality solutions (and cheap) will appear, make less money.
If we expect “a perfect moment,” we can fall behind eternity.
What strategies can happen to business learners?
1. Use gradually, starting with low solutions
You don’t have to replace the rest of the program at the same time. We can start a little:
- Automated the general functions (to produce tests, answering constant questions).
- Customized learning (variable lessons associated with employee level).
- Using chatbots support (instead of FAQs).
This approach reduces the risk and allows a gradual integration of new technologies.
2. Variable Buildings: Leave Renewal Room
If ai solutions are used in Modar structure, they can be cleaned as new technology. For example:
- Using Apis instead of integrated models.
- Developing easily adhering platforms.
This reduces the system’s risk should not end.
3. The same techniques: Text and evaluation
We can introduce certain driving projects with different technologies:
- One group of workers trains using Chatgpt.
- Another with traditional LMS.
- Thirdly with hybrid solutions.
After 6 to 12 months, we can compare results and select the best option.
4. Monitoring styles and ready to be immediately implemented
Instead of waiting, we can:
- Create an internal group following new EDTTCH skills.
- Create relationships with merchants to get early access to a new development.
- Hold Hackathons to test new tools.
This keeps us going back without investing in expired technology.
What if the wait is very dangerous? History is aware of the many examples of losing companies due to the determination:
- Kodak invented a digital camera but did not improve, and they began to smoke.
- The Nokians reign a telephone market but could not comply with smartphones.
On the other hand, there are examples of pre-approval: META (Facebook) has invested billions of millions of millions of millions, but technology is not ready for abundance yet.
5. The most important thing: new products require more than technology
Most importantly is what the team’s experience and internal technology.
When “the whole time” we arrive, you will need workers who know exactly what to do and how. Those already “learned from mistakes” and understand all the steps. Such technology will only appear if your organization works diligently in developing AI in learning.
Balance between rename and pragmatism is the key to success.
Conclusion: The correct strategy
- Don’t wait for “a perfect moment” -And you never come.
- Start smaller flight projects, exams.
- Build changing systems to easily be updated.
- Monitor tendency and ready to measure immediately.
Just as the space out, the best option is not extremely extremely exaggerated but reasonable balance between the act and adaptation.
AI must be used in combined learning now, but easily, with the ability to immediately renew. Besides, there is a risk of fall afterever or to spend services.
What strategy do you prefer?