The sudden emergence of Artificial Intelligence tools may have shocked many since various algorithms have been in the works for quite some time now. Despite this prior knowledge, many were still unaware of the magnitude at which these tools would eventually be released.
ChatGPT, released in November 2022, has sparked a lot of debate. Primarily, can the free conversational chatbot write essays? Could it eventually leave writers unemployed? How could it be used to improve research projects? Might this technology be strong enough to substitute humans?
In March 2023, in response to ChatGPT’s release, Microsoft made a huge $14 billion investment in OpenAI – its developer. Concurrently, Google launched its alternative tool, Bard. Nowadays, many generative AI tools are yielding content of all kinds.
OpenAI has developed two special tools: GPT-3 and Dall-e. GPT-3 can generate written content for any object or concept, while Dall-e produces original artwork. Other AI tools can create videos, podcasts, logos, and more.
Despite the naysayers, Professor Richard Dazeley of Deakin University’s School of Information Technology emphasizes not disregarding the strength potentially generated from generative AI tools. He warns that new technological development should not be dismissed.
Professor Richard Dazeley says:
‘The next generation is supposed to be far more accurate in what it is predicting,’
‘I’m not particularly into super intelligence fearmongering, but we’re typically predicting shorter timeframes for significant improvements.’
What is Generative AI? Exploring The Basics Of Artificial Intelligence
AI has been making a lot of headlines, worrying some about the jobs it may replace. However, before getting anxious about it, let’s understand what we are dealing with and what powers AI. First, we should take a step back and comprehend the underlying mechanisms.
Professor Richard Dazeley continues to say:
‘AI just a fancy term for algorithm,’
‘The main difference is the perception of these tools – that they produce behaviour that appears to be intelligent. What it generates is not a duplication of something somebody else has done; it’s original in its own sense.’
Generative AI entails utilizing generalizations for its functioning. It must be noted that these tools’ decision-making capabilities are based on pre-existing conceptions and patterns.
Prof. Dazeley went on to say:
‘It studies billions of examples and builds up its own invented model of what those examples represent,’
‘In the case of ChatGPT, if you ask it a question, it considers the way thousands of people have answered that, then generates something that is a generalisation of that answer.’
Generative tools make it possible to determine, with a certain level of probability, what will likely come next by employing predictive technologies. This ability to generate predictions is the source of the term ‘generative.’
Prof. Dazeley adds to say:
‘In the case of the image generation tools, it starts with a random thing then corrects until it forms an image that it associates with the answer to the prompt you’ve provided,’
Understanding The Limitations Of Generative AI Technology
According to Prof. Dazeley, generative AI’s “fundamental flaw” is rooted in its reliance on generalizations, preventing it from being entirely reliable – even with improved processing capabilities.
Prof. Dazeley continues to say:
‘The generative AI model cannot be perfectly accurate guaranteed all the time, because as soon as you have something that generalises, it’s going to get specifics wrong,’
There can be a challenge for those engaged in narrow fields or those looking to explore new information: machine learning algorithms usually rely on substantial data sets to generalize; thus, any domain with limited knowledge may pose difficulties. This holds for businesses, scientists, students, and others working in various areas.
Prof. Dazeley went on to say:
‘It’s showing it’s good at fairly generalised skills, but where these systems will struggle is any time you’re doing something quite specific and need to be accurate,’
Exploring Generative AI: What’s Next In The Field?
The prospects of generative AI include seamlessly combining ChatGPT and Dall-e with other services, such as allowing ChatGPT to perform Google Searches or Siri to start behaving conversationally like the former. This would create an experience that feels more like real intelligence.
Prof. Dazeley adds to say:
‘At the moment its just using a model to predict how a human might respond, but this would mean having the system taking your prompt and formulating a search query itself, finding what it needs, then finding a correct and specific answer for you,’
‘In a research sense, these things exist now. In a commercial sense, companies are still in the process of testing to make sure they’re not releasing something too inaccurate. I expect we’ll see integrated AI systems probably within a year or two.’
Will AI Put You Out Of A Job? Find Out Now!
Although he does not subscribe to fearmongering, Prof. Dazeley believes young people should consider the advancements of AI when deciding on their careers.
Prof. Dazeley says:
‘Anything that requires high-level intelligence is probably safe for a good period of time, plus there’s always new jobs,’
As technology advances, engineering skills that utilize AI are becoming increasingly sought after. According to the expert’s prediction, prompt engineering with AI capabilities is in high demand.
Prof. Dazeley went on to say:
‘Rather than doing the data analysis, it’s how do you ask the right question to the AI so you get the answer that you want. We used to have training on how to do Google Search, but we’ll now need training on how to write questions for AI.’
The future of AI holds immense promise. Through continuous innovation, collaboration, and ethical frameworks, we can leverage AI technologies to transform industries, improve lives, and push the boundaries of human knowledge. Let us embrace this new era with optimism and responsibility as we unlock the next wave of AI advancements beyond ChatGPT.
Source: this.
