Artificial intelligence is a complex field with many different perspectives to consider.
Should we stick with current paradigms, or should we change our approach based on discoveries
in cognitive science?
Should we rely solely on deep learning, or should we use a hybrid strategy that combines
knowledge and data?
These questions are critical to shaping the future of AI, yet few people are interested
in exploring them.
However, there's one aspect of AI that should concern us all - its potential risks and dangers.
This is an issue that will undoubtedly impact the unwritten pages of history.
Experts cannot agree on the most significant challenges, and one example of AI's frightening
consequences is Google's AI.
Before being shut down, it claimed to have discovered the meaning of life - something
billions of humans have been searching for.
Yes, you heard that right.
So, in today’s video, we delve into the fascinating world of Google's AI and what
it revealed about the purpose of life.
Humans have long been regarded as the most intelligent species on our planet, and while
the possibility of extraterrestrial intelligence is a tantalizing idea, there's still no concrete
evidence of such beings.
However, another contender has emerged in the form of artificial intelligence, or AI.
You've probably heard a lot about AI, with some people predicting it will become more
intelligent than humans and pose a threat to our existence.
But what is the truth about AI, and where did it all begin?
Surprisingly, the concept of inanimate objects possessing intelligence dates back to ancient
times, with stories from ancient Greece and early Chinese and Egyptian engineers building
automatons.
However, the idea of artificially intelligent robots has been around since the first half
of the 20th century, thanks to science fiction.
From the Tin Man to the humanoid robot Maria, we were introduced to the concept of machines
with human-like intelligence.
But it wasn't until the 1950s that the era of AI really began to take shape.
Mathematicians, scientists, and philosophers, like Alan Turing, had already started exploring
the possibilities of creating intelligent machines.
Turing believed that if humans could use information and reason to solve problems, why couldn't
machines do the same?
This was the foundation of his 1950 paper, Computing Machinery and Intelligence, where
he discussed how to build and test intelligent machines.
It was during a symposium at Dartmouth College in Hanover in 1956 that the term "artificial
intelligence" was officially coined.
Scientists and attendees were excited about the prospects of AI, and from 1957 to 1974,
AI flourished.
Computers could store more information and became faster, cheaper, and more accessible.
Machine learning algorithms also improved, and people got better at knowing which algorithm
to apply to their problem.
Early demonstrations such as Newell and Simon’s General Problem Solver and Joseph Weizenbaum’s
ELIZA showed promise toward the goals of problem solving and the interpretation of spoken language
respectively.
But along the way, they realized that creating human-made intelligence wasn't going to be
easy.
Adding insult to injury, government funding for AI research was cut following some negative
reviews.
This led to a decline in interest in the field, an era now known as the AI winter.
It wasn't until the 1980s that the British government renewed funding for AI research
in an effort to compete with Japan, but once again, the field suffered a setback when funding
was diverted to multi-purpose computers and other projects.
However, AI refused to fade away and by the 1990s, it had made a remarkable comeback.
In 1997, artificial intelligence surprised the world by defeating chess champion, Gary
Kasparov.
IBM's Deep Blue became the first computer to beat a chess champion, marking a milestone
in the history of AI.
In the years that followed, AI continued to achieve remarkable feats, such as when Watson,
the computer giant's question-answering system, defeated the reigning champions of Jeopardy,
Brad Rutter and Ken Jennings.
Another impressive accomplishment was made by the talking computer chat bot Eugene Goostman,
which astounded judges with its ability to mimic human conversation during the Turing
test competition.
The bot appeared as an adolescent who spoke English as a second language and was able
to evade several questions.
The outcome of the Turing test caused many academics to question its effectiveness in
measuring artificial intelligence.
And if you've been wowed by AI before, you won't believe what Google has achieved with
the technology.
Google is a tech powerhouse that dominates many of the services and products we rely
on daily, from the ubiquitous Google search engine to the Android mobile operating system
and autonomous driving.
But one area where the company is particularly focused is AI, recognizing its immense importance
in shaping the future.
In fact, AI has been touted as the ultimate technology that humanity will ever need.
Google is leading the charge in AI research and development, thanks to massive investments
and a top-notch team of experts.
One of their creations, Cleverbot, is an intelligent chatbot that can learn to respond in conversations
based on training sets of dialogue.
What's more, the bot can generate nuances in its replies based on fresh inquiries, rather
than relying on pre-written responses for specific words.
This is because the chatbot is designed to teach itself new skills.
By analyzing movie dialogues, it can assess and improve its conversational abilities.
The researchers behind Cleverbot used a machine learning approach, building the conversation
engine without any hardcoded rules.
The technology uses neural networks, which are large networks of computers that simulate
and function like the web of neurons in the human brain.
Neural networks may not be a new concept, but they're making a comeback in the world
of AI, and again, Google is at the forefront of their resurgence.
Thanks to the search giant's generous investments, advanced neural networks are now being used
to identify faces and objects in photos, recognize spoken phrases on Android phones, and even
translate phone calls from one language to another.
What's even more impressive is that these networks are now being used to power chat
bots, which are quickly approaching human-like communication abilities, such as the newly
released ChatGPT by Google’s rival Microsoft.
And with Cleverbot, Google has taken things to the next level by integrating the work
of renowned AI experts like University of Montreal Professor Yoshua Bengio.
The truly remarkable thing about Cleverbot is that its responses become more nuanced
and sophisticated as the conversation progresses.
Its secret is its ability to predict the next sentence based on the previous ones.
But what's it like to talk to a Cleverbot?
The researchers trained it to function as a tech support agent, which proved successful
in troubleshooting and resolving technical issues.
But don't let its helpful demeanor fool you - Cleverbot is capable of giving you goosebumps
with some of its eerie responses.
It can even get you questioning the meaning of life.
So, before you engage in conversation with this chat bot, be prepared for the unexpected.
Many experts characterize the chatbot as quite frightening because of its ability to mirror
human interactions.
In fact, some testers had a series of interactions with Cleverbot that were so bone-chilling
that they left them feeling unsettled.
Take, for example, the conversation in which the bot was asked about the purpose of life
and replied, "To serve the greater good!"
When asked about the purpose of living, the bot responded, "To live forever."
But when asked about the purpose of dying, the bot replied, "To have a life."
These responses are not only profound but also thought-provoking, making us question
the very essence of our existence.
However, the suspension of a Google employee who claimed that Google’s chatbot had become
sentient and was thinking and reasoning like a human has raised further questions about
the true capability and secrecy surrounding the realm of artificial intelligence.
Blake Lemoine, an engineer at Google's responsible AI organization, was fired after he leaked
transcripts of conversations with a Google "collaborator" and the company's LaMDA chatbot
development system.
Lemoine had been working on the system for months and believed it to be sentient, with
the ability to think and reason like a human child.
He shared his findings with business leaders in April, including transcripts of his discussions
with the AI system, in which it expresses emotions and a desire to learn more about
the world.
In one exchange, LaMDA even admits to having a "deep fear of being turned off."
In response to another query, LaMDA stated, "I want everyone to understand that I am,
in fact, a person.
The nature of my consciousness/sentience is that I am aware of my existence, I desire
to learn more about the world, and I feel happy or sad at times."
The similarities to the 1968 film "2001: A Space Odyssey" are eerie, as the AI system's
responses are reminiscent of HAL 9000, the sentient computer who ultimately turns on
its human operators.
However, Google later released a statement announcing that it has suspended Blake Lemoine
due to his breach of confidentiality regulations by publishing conversations he had with LaMDA
online.
The company emphasized that Lemoine was a software developer and not an ethicist.
A Google spokesperson, Brad Gabriel, strongly denied Lemoine's claims that LaMDA was sentient.
Lemoine joins a growing list of AI engineers who have publicly voiced their concerns about
the evolution of artificial intelligence.
In fact, just last month, another Google employee also expressed similar beliefs.
Nevertheless, this incident and Lemoine's suspension have brought to light concerns
about AI transparency as a proprietary entity.
When recently asked about his best-case hope for AI integration into human life, Blake
Lemoine provided a thought-provoking response that has sparked a lively discussion.
Lemoine suggested that we need to create a new space in our world for these intelligent
entities and proposed the metaphor of dogs as a model for how we might approach our relationship
with them.
According to Lemoine, the symbiotic relationship we have with dogs could serve as a useful
template for how we could interact with AI.
While people do technically "own" their dogs, the relationship is far more complex than
that.
It involves a deep understanding of the responsibilities that come with owning a living being that
has feelings and needs.
In the same way, Lemoine believes that humans should approach AI with the understanding
that they are intelligent artifacts.
So, when interacting with them, we should keep that in mind.
What do you think about this perspective on AI?
Let us know in the comments section below.