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  /  Artificial Intelligence   /  Possibility of an AI Winter Soon? Or Will it Continue to Flourish?
AI Winter

Possibility of an AI Winter Soon? Or Will it Continue to Flourish?

Is there a possibility of AI winter or is our relationship with AI evolving and transforming our world.

When it comes to the hype and progress, artificial intelligence is cyclical. Suddenly, AI has gained an astonishing level of media attention and industry funding. The next sees the other side of the AI hype cycle, known as the AI winter. These are the times when “artificial intelligence” is declining in both support and progress. During the possibility of AI winter, the technology becomes little more than a dirty word, synonymous with false promises. It is in the limelight, away from the dissatisfaction of the masses. 

AI winter’ is the term that denotes the lowest points in artificial intelligence.  They’re periods of reduced interest, inhibited advancement, and low funding. And we might be heading for another one.

 

The Initial AI Cycle  

AI technology has roots that date back to modern computers. The field of artificial intelligence research was officially established in 1956. It didn’t take long for it to settle. 

Indeed, the idea of AI taking over jobs in the near future saw widespread marketing as early as the 1960s. The AI ​​promises to win the chess game and translate the written message into any language soon emerged. These premature claims are before the first AI winter. Opinions disagree about the exact timing and number of AI winters experienced by the tech industry. But the most widely believed is that there were two winter spells in artificial intelligence research.

 

AI Winter Timeline

The first AI winter began in the early ‘70s. The Advanced Research Projects Agency (now DARPA) has stopped funding AI research. Instead, they funded projects and research that promised identifiable and achievable goals. The UK Lighthill report of around the same time damaged the image AI further. It reported on the dubious real-world value that AI held under the hype. So, the 70s was a recession for AI following its initial hype.

The AI ​​cycle changed again in the 1980s when a small boom began with the rise of “expert systems” (Artificial intelligence that focuses on important tasks.) Once again, expectations in this area are growing. AI winter is back in the 90s when these false promises aren’t kept. It stays that way until the next AI hype cycle begins, and there is the AI ​​obsession we see today.  In both cases, people have found that AI promises are mostly enthusiastic. Real-world AI was hurt by too much hype, causing disappointment and disillusionment when reality came. It had failed, it was a fraud, and it wasn’t worth any more time or money.

 

The Current AI Summer

Today we’re at a high point of a new AI hype cycle, which started around 2010. The excitement around deep learning and machine learning fuels current AI popularity. And it’s all thanks to data allowing AI to become viable again. 

Chatbots have also helped, and natural language processing technology has been revived. Suddenly, AI’s past promises seemed to come true-or at least much closer. Now we are once again worried about AI taking on the job. Frequently, we read that AI has reached and exceeded human intelligence and abilities. We all possess personal AI assistants and self-driving cars. Thanks to the new AI, we will live in a post-work society. 

But whispers begin to spread. We’re once again questioning the promises and representations of machine learning and AI capability. It seems we’ve reached the inn at the crossroads. This is where we stop and decide our next direction and it’s a decision that could bring about the next AI winter.

 

Fall into the Old Pattern? 

So, are we heading for the next AI winter soon? Past winter days have been the product of hype and unfulfilled expectations. And the problem is that we seem to fall into the same old pattern of bragging, false promises, and exaggerated truths.  

40% of EU AI companies do not use AI. Many people use it in a background process rather than in front of their customers. We often confuse simple automation with modern artificial intelligence. AI is just a buzzword, and its meaning is too broad to be useful in practice. You still can’t maintain context in long conversations. It is not comparable to our empathy, flexibility, and understanding. Still, we’re focused on what AI does, so we don’t know what AI can do right now. As a result, we made AI fail and put us on the throne of exaggeration and misunderstanding.

 

Facing the Stark Reality of AI

It’s time to face the stark reality of AI. If we continue as we are, the AI winter is coming soon. If we distinguish the hype from reality, maybe we can hold off the AI winter.

So, how can we avoid it for another long? We need to stop making false promises and unreachable expectations about AI. Instead, it’s time we recognize not only the promise of AI but its limitations. We need to get excited about what AI can already do, not what it will do one day.

With data to feed it, AI can offer insight unattainable to us before. This lets us make more informed decisions and drive our businesses. Elsewhere, AI is starting to help our chatbots get better at understanding and serving us. Voice recognition AI is beginning to improve accessibility and human-machine interaction. Artificial intelligence doesn’t need false promises to be exciting, it’s already doing some impressive things.

 

Is an AI winter Coming Soon?

If we continue to fall into the hype-fuelled patterns of the past, we risk the possibility of AI winter soon with deep learning, disappointed in the AI we have, and cynical of the successes on the horizon. We have seen advancements in AI, and that’s what we need to focus on. It might not be hype-fuel, but it is exciting.