Whilst the world jizzed over ChatGPT, OpenAI’s AI chatbot, some of us had been using everything from Otter to Gmail for a while. ChatGPT seems almost magical in its ability to provide answers to a wide range of questions. But AI is way more than just chatbots – it’s a diverse landscape with immense potential. While having AI-powered chatbots help you with tasks or generate captivating images is exciting (think of the fingers), the true power of AI goes beyond, potentially reshaping economies on a massive scale. McKinsey Global Institute estimates this potential impact at a staggering $4.4 trillion annually for the global economy.
How should you get started with AI? Why would you even bother? Are the old ways really the best? No. Well, sometimes yeah. But mostly ChatGPT and all its happy money-generating children are there to make you more productive. I can feel through these words I write, that you already feel more productive. Amirite? Here’s some cool ideas for ya.
Low Hanging Fruits
Want to get started quickly? These bots will help you to do stuff if you ask the right questions. I’ve added a couple to get you started.
Customer Support Chatbots: Companies use AI-powered chatbots to provide instant assistance to customers, answering common queries and guiding them through troubleshooting steps.
“Provide one paragraph about our return policy [pasted here] using a fun yet informative tone.”
Content Generation: Journalists and content creators leverage AI to draft articles, reports, and summaries, saving time and generating content ideas. “I need to write an article about AI covering chatbots and generative AI, please provide it in the style of Kelly Vero.”
The Segmenters (these were not selected for Harry Potter villains, sadly)
I loved working with DICOM and supercomputers, but unless you know what to look for, you won’t be able to tell AI what it is you need. That said, segmenting is one of THE most relevant AI processes because, like ripping a piece of paper strip by strip you want a computer that can put it back together and tell you what the data says.
Medical Imaging Diagnosis: Deep learning models analyse medical images like X-rays and MRIs to assist doctors in detecting diseases at an early stage, enhancing patient care.
Autonomous Vehicles: Deep learning algorithms process real-time data from cameras and sensors in self-driving cars to identify objects, pedestrians, and road signs, ensuring safe navigation.
The Freuds
Is there anything better than not thinking? Thinking makes…
