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How Artificial Intelligence with Multiple Skills look like? – Analytics Insight

AI scientists have discovered methods enabling machines to see, hear, speak, and write
So far, we have seen Artificial Intelligence doing wonders in ways innumerable. Sectors like Healthcare, defence, education, travel and tourism to name a few – you name it and the advancements brought forward by Artificial Intelligence will leave you stumbled. With every passing day, researchers are trying every possible way to equip machines with even more skills so that machines stand the potential to deliver improved results with even better accuracy and precision.
Artificial Intelligence scientists went a step ahead in this technological driven world by discovering methods that’d enable the machines to not just see (as it was developed initially) but also to hear, speak, and write.
It has more or less been the case wherein Artificial Intelligence programs are constructed with a motive to cater to perform one activity at a time. Consider the example of a mannequin. A mannequin that’s powered by NLP stands the potential to manipulate phrases. If there’s an additional feature built in, the researchers fear that the original purpose might not be served. Yet another example is that of laptop-vision and audio-recognition algorithms which evidently cater to recognise vision and speech. On the contrary, they cannot use language to explain them.

How AI with multiple skills look like?
Gone are the days when it was believed that the sole purpose of deploying Artificial Intelligence would be lost if there are many areas to address. Today, the situation seems to have taken a 360 degree turn. The researchers are hopeful that when models are built with multiple areas to cater to, that might result in an advanced and sturdy AI system that is capable enough of dealing with issues with utmost precision. With this, the machines can be but to the best possible use to deal with situations, no matter how complicated they are.
Back in September, researchers of the Allen Institute for Synthetic Intelligence, AI2, made into the headlines. They came up with a mannequin that may generate an image from a text caption. All this throws light on the ability the algorithm has when it comes to affiliating phrases with visible data. On the same lines, researchers of the College of North Carolina, Chapel Hill, had put in all efforts to develop a method that’d incorporate images into existing language models.
With the advancement in technology, the algorithms cater to a lot of areas. OpenAI’s GPT-3 needs no special mention in this aspect. The name is such because OpenAI used these concepts to increase GPT-3. Replicating language manipulation in combination with sensing capabilities would yield fruitful results – this is what the scientists anticipate. Point being – the first step has already been taken. The outcomes delivered are easy bimodal fashions, or visual-language Artificial Intelligence. It was just a few months back that the lab launched two visual-language fashions. One focuses on hyperlinking the objects in a picture to the phrases that describe them in a caption. The other generates photos mostly on the basis of a mixture of the ideas it has discovered.
We are now at a stage wherein multimodal programs can create extra advanced robotic assistants. With these models in place, it is possible to navigate, work, finish tasks despite constraints, etc. However, the researchers are not willing to stop here. One such example is that of AI2 lab. This lab is working to add language and incorporate extra sensory inputs, like audio and a lot more into machines so that they can perform complex tasks as well.
In the future, it is important that the multimodal programs are in a position to overcome at least a few of the AI’s greatest limitations. Work in the aspect of making Artificial Intelligence a lot safer and easy to use should be given importance to. In a nutshell, multimodal programs can grow to be the primary AIs that we can rely on without any doubt.

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