AI and Generative AI- the difference and 5 examples of each.

AI and Generative AI, nothing seems to be talked about more than both.?But before unpacking how to tap into this power technological trend and breakthrough, let’s first define both terms.

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AI, or Artificial Intelligence, refers to the use of algorithms and computer systems to perform tasks that would ordinarily require human intelligence. AI is used in a variety of applications such as voice recognition, image analysis, and machine learning.

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On the other hand, Generative AI refers to a type of AI that uses deep learning neural networks to create something new or generate output. Rather than simply performing tasks, generative AI is focused on producing original content, such as music, art, or even human-like conversation.?Essentially it is a type of machine learning that involves creating new content, ideas, or images that do not exist in the world. It can be used to generate new product designs, create personalized marketing campaigns, or even generate entirely new business ideas.

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A little history on AI

Although we have only begun hearing about AI Artificial Intelligence (AI) in the past decade or so, it has been a focus of research and development since the 1950s, with pioneers like John McCarthy, Marvin Minsky, and Claude Shannon paving the way for early breakthroughs in the field. These early efforts focused on developing programs capable of reasoning, problem-solving, and learning from experience.

In the 1960s and 1970s, AI made significant strides, with the invention of machine learning techniques, natural language processing systems, and expert systems. However, progress in AI stagnated in the 1980s as computing power was limited, and funding for AI research was cut.

The 1990s brought renewed interest in AI, this time with a focus on developing intelligent agents capable of interacting with the environment. Researchers began developing AI techniques like neural networks and genetic algorithms, which allowed machines to learn from experience and optimize their behavior based on desired outcomes.

In the early 2000s, AI started to gain commercial viability with the development of voice assistants like Siri and Alexa. These systems use natural language processing and machine learning to understand and respond to user requests.

Around this time, in 2016, ChatGPT was invented by OpenAI. ChatGPT is a generative AI model that uses natural language processing to generate human-like responses to text prompts.?These models can create original content, such as images, text, and videos. These systems use techniques like deep learning and neural networks to analyze large datasets and generate new content.

5 examples of AI:?

1. Virtual assistants such as Siri and Alexa that use natural language processing to answer questions and perform tasks.

2. Image recognition software that can identify objects in images and videos.

3. Fraud detection systems in banking that can identify suspicious behavior and prevent fraud.

4. Smart home devices that can turn on lights, adjust thermostats, and perform other tasks based on user preferences.

5. Chatbots that can hold conversations with humans and provide customer service.?

5 examples of Generative AI:

1. The popular app, Prisma, which uses AI to transform photos into works of art.

2. The music composition software, Amper, that creates unique soundtracks based on user settings.

3. The Google DeepMind project that created AlphaGo, a computer program that beat a human champion at the board game Go.

4. The Turing test, which uses AI to generate conversational responses that closely mimic human speech.

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5. A recent project that used generative AI to create a new Rembrandt painting that was nearly indistinguishable from the artist's authentic work.

While both AI and Generative AI are types of artificial intelligence, they differ in their focus on task performance versus content creation. While we’re simply relieved to have basic AI handle many tasks, the truth is we’re only just beginning to tap into the potential of AI with it focused more on content creation.?With the ongoing development of these technologies, we can expect to see continued advancements and exciting new applications in the future.

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By utilizing Generative AI, corporations can differentiate themselves from their competitors by creating unique and memorable experiences for their customers. It can also help companies to optimize their services by generating solutions to complex problems that would be difficult for humans to solve.

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In addition, Generative AI can help corporations streamline their operations and reduce costs. For example, it can be used to generate realistic simulations of production environments, allowing companies to conduct virtual testing and refine their processes before implementing them in the real world.

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Overall, Generative AI is a powerful tool that can help corporations improve their services and remain competitive in an increasingly complex and demanding business landscape. Learn to harness it!