With the emergence of products like Chat GPT, Amazon LLM, and Google Bard, Generative AI has firmly established itself as the next big thing in smart technology.
Definition: Generative artificial intelligence (AI) is at the forefront of technological innovation, changing the way humans and machines interact and fostering a new era of creativity. Unlike traditional AI systems that rely on predefined rules, generative AI leverages advanced algorithms to generate original content, including text, images, and music.
One of the key aspects of generative AI is its ability to learn and mimic patterns from vast datasets, allowing it to create content that closely resembles human-created material. The technology has applications in a variety of fields, from natural language processing to image synthesis. OpenAI's GPT (Generative Pre-trained Transformer) models, such as GPT-3, demonstrate the prowess of generative AI by generating coherent and contextually relevant text based on input prompts.
Looking to the future, advances in generative AI hold the promise of groundbreaking applications yet to be explored. As research and development in this field advances, society must understand the ethical implications and establish guidelines to ensure the responsible and beneficial use of this powerful technology. Generative AI is a testament to the ever-expanding capabilities of artificial intelligence, pushing the boundaries of what machines can achieve and opening up new dimensions of human-machine collaboration.
To be clear: the above definitions were generated by ChatGPT.
Now, let’s move on to the non-AI-generated discussion…
The arrival of AI in our world has raised more questions than answers, but the biggest question may be: How can GenAI technology be most effectively applied for end users?
Admittedly, this is a very clever approach, but unless you’re a student looking to shave off your weekly essay assignments, identifying the application opportunities for AI isn’t easy.
Generative AI: How will it impact the future of life at home and on board?
utility
The first and most readily available applications of AI are already in use around the world through devices like Alexa, Google Home, and Apple HomePod. Aptly named smart speakers, these use AI to listen to your questions and commands and then provide verbal responses and in some cases control actions – essentially virtual assistants in your home that handle everyday tasks like finding information or pressing buttons.
All of this is very clever, but they're not actually “producing” anything, they're simply responding to binary instructions or questions with defined responses.
The next evolution will be the dynamic integration of third-party devices using APIs. Instead of users having to “integrate” a new IoT-connected system, such as a new “smart” refrigerator, AI will enable automatic discovery and integration.
example:
“Hi John. I see you've got a new smart fridge. Want me to take a look and create a shopping list for you?”
GenAI also unlocks the possibility for homeowners to program complex routines. Currently, these macro-style actions must be defined and programmed by the system integrator. AI unlocks the possibility of translating voice instructions into a new set of scheduled actions.
For example: “Alexa, every night at 9pm, announce it's bedtime for the kids, dim the upstairs lights, turn on the hallway light, and turn on the bedroom fan.” Alexa will then automatically program that set of actions to occur at the specified time every night.
AI is already being used in security applications such as next-generation CCTV cameras that use video analytics for motion detection. These cameras could also act as “identifiers” using facial recognition, moving the application even closer to the generative AI spectrum. When paired with a speaker, the camera could trigger a “welcome” greeting or a warning such as “This premises is private property, you have been identified by a camera, please leave immediately.”
conversation
The next evolution of smart hubs will be to introduce conversation into the interaction. The use of additional sensors such as cameras and motion detection, along with machine learning algorithms to profile human users, opens up huge possibilities for making virtual assistants even more useful companions.
example:
(walking into a room) – “Hello, John. Welcome back.” (anticipatory behaviour) – “Shall I play some music?” (knowledge-based conversation about the daily commute) – “How was the traffic? I heard there was a lot of traffic on the A63 this afternoon.”
These next-generation devices are already in development, with the aim of turning your home smart hub into a virtual companion with a personality.
personality
One of the biggest challenges in robotic speech generation is making it sound natural: humans use intonation, temperament and volume to articulate speech, so virtual assistants need to incorporate this into their speech patterns to be more effective.
Amazon calls this project LLM (Large Language Model). While humans often pause during conversations to gather their thoughts or emphasize a point, these cues can be very difficult for AI to identify. This new engine adapts to these common and natural pauses and hesitations, making conversations smoother and more natural.
This means that the future Alexa will adapt to your cues and adjust its responses and tone like a human conversation: Ask Alexa if her team won and she'll respond with a joyful tone if they did and a more empathetic response if they lost; ask Alexa for her opinion and she'll respond with a more enthusiastic tone, like a friend giving their opinion.
While this digital personal assistant may be appealing to consumers who can't afford to hire household staff, it may not be of much use in the yachting industry, where crew members essentially play this role.
content
The potential uses of GenAI are endless, with one recent use being the creation of digital art and photography. The popularity of Generative AI comes with concerns about ethics, misuse, and quality control. Because Generative AI is trained on existing sources, including those that are not verified on the Internet, it can provide misleading, inaccurate, or false information. Even when sources are provided, they may contain inaccurate information or be linked incorrectly.
summary
GenAI as an emerging technology is both exciting and scary: the potential for increased efficiency, learning, and productivity is great, but big questions remain about verifying information and trustworthiness.
When used in the public domain, GenAI also carefully toes the boundaries that define acceptable privacy ethics. If they start using technology to eavesdrop or monitor guests in a hotel or yacht environment, some sort of waiver or NDA agreement would have to be signed to protect the data collected. This isn't as much of a concern in a private home where the system is owned by the owner, but what do Google, Amazon and Apple do with the data they collect?
The best way to conclude this article is to think about the word “knowledge.”
knowledge
Definition: Perception or knowledge gained through experience of facts or circumstances.
In the GenAI world, it has become so easy to generate and spread misinformation that it is no longer clear what is real/true and what is false.
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