FINAL WORD collaboration that can identify patterns the human eye cannot see , providing data-based insights , analysis , predictions and suggestions . If you start to view AI as a way to improve business from a bird ’ s eye view , you can begin to harness its full potential .
For businesses today , it is not a matter of if they will adopt AI within their workplace , but rather , when . But with this comes the entirely unchartered waters of ethics and accountability – and whether the robots really are coming for jobs . As AI technology excels at a pace that laws and legislators cannot keep up with , the responsibility for ethics and accountability currently lies with each individual user .
As AI can process data at a rate far faster than anything we have seen before , transparency becomes vital in terms of how the data is sourced , analysed , and implemented . Neeley cites the large language models , LLMs such as OpenAI ’ s Chat-GPT or Microsoft ’ s Bing , which are trained on massive datasets of books , webpages , and documents scraped from across the Internet : OpenAI ’ s LLM was trained using 175 billion parameters .
This opens AI up to unintentional bias , as it is trained on data sets that may not be representative of the global population . To avoid this bias being embedded into the AI systems , developers are being called on to include more diversity in their data sets and in the
While Elon Musk previously called for a pause in the creation of AI digital minds , along with Steve Wozniak and Emad Mostaque , he now feels that ship has sailed .
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