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The rise of Gen AI: Pros and cons, prospects and will it take our job?


Generative AI, a subfield of artificial intelligence, has rapidly emerged as a game-changer across various industries. Unlike traditional AI focused on analysing data, Gen AI excels at creating entirely new content, ranging from text and images to music and even code. Recently, a Gen AI based startup, ElevenLabs raised $80M Series B at 1B valuation, which also shows how the Gen AI is being valued even more these days.

This transformative capability sparks both excitement and apprehension, raising questions about its potential impact on our world. In this exclusive article, we delve into the potential of Gen AI, exploring its research background, advantages and disadvantages, key players, diverse applications, and exciting future prospects.

From research labs to real-world applications

The foundations of Gen AI lie in deep learning algorithms, particularly Generative Adversarial Networks (GANs). Introduced in 2014, GANs involve two neural networks pitted against each other: a generator continuously creates new content, while a discriminator tries to distinguish it from real data. Through this competitive process, both networks refine their abilities, leading to increasingly realistic and creative outputs.

Since its inception, Gen AI research has flourished, fueled by advancements in computing power and the availability of massive datasets. Landmark research papers like “Attention Is All You Need” (Vaswani et al., 2017) laid the groundwork for Transformer models, now widely used for text generation and translation. Similarly, Diffusion Models (Ho et al., 2020) have demonstrated remarkable image generation capabilities, blurring the lines between reality and AI-created visuals.

Will AI take over our jobs in future?

When asked, with job roles like Prompt Engineers on the rise, do you foresee Gen AI eventually taking over these positions as well, Mike Albertshauser, co-founder at BLOOM, an audio erotica startup that uses voice AI told TFN:

“Generative AI is an incredible tool. It’s unlocking new customer experiences and making the way we work more efficient. But I don’t think we will ever fully replace or replicate the creativity or passion that humans have, particularly in the creative industries – nor do I think we will ever stop needing a “human in the loop” where we are building generative AI. Our roles at work will continue to change as AI becomes more sophisticated, but I don’t believe we’ll ever see AI taking over every kind of job role. This is particularly true in the creative sector.”

When asked about what specific measures do you think would enhance the security of Gen AI and mitigate potential issues? He further added, “In the case of voice AI, it’s important to ensure we’re protecting the humans involved. For example, if a voice actor’s voice is being used to create a synthetic voice, that voice actor needs to be fairly paid when their likeness is used. Whilst we wait for tighter regulation, it’s on individual companies to make sure they’re doing the right thing and looking after the people that work for them.”

“At BLOOM, we’ve worked closely with the voice actors involved in our AI “BLOOM Chat” feature to ensure they’re comfortable with the commercial arrangement and to pay them residuals. We’re also only using AI in features on our platform where it would be impossible for a human to do that work. Where we can still use voice actors’ real voices, we will always still use human voice actors. We want to continue to respect and support the talent of creators, whilst exploring innovative new technologies that can enhance the user experience. It’s important for all companies using or producing generative AI to strike that balance.”

Pros and cons of Gen AI

The potential benefits of Gen AI are vast. It can automate content creation tasks, revolutionising industries like advertising, design, and entertainment. Imagine AI generating personalised marketing campaigns, designing unique clothing lines, or composing captivating movie soundtracks. Gen AI can also facilitate scientific discovery by generating novel materials, drug candidates, and protein structures, accelerating research and development processes.

However, concerns regarding the misuse of Gen AI are equally valid. The ability to create deep fakes, highly realistic AI-generated videos or audio recordings, poses a significant threat to online security and trust. Additionally, the potential for bias amplification in AI models trained on imbalanced datasets raises ethical concerns, requiring careful mitigation strategies.

Leading the charge: Top Gen AI companies

Several companies are at the forefront of Gen AI development, each with its own unique focus and offerings. Here are a few prominent players:

  • OpenAI: Known for its advanced language models like GPT-3 and Dall-E 2, OpenAI pushes the boundaries of text and image generation research, actively engaging with ethical considerations.
  • DeepMind: Backed by Google, DeepMind focuses on developing general intelligence and has made significant contributions to Gen AI research with its AlphaFold protein structure prediction system.
  • Stability AI: Focused on democratising access to Gen AI tools, Stability AI developed Stable Diffusion, a powerful image generation model accessible to a wider audience.
  • Jasper: This AI writing assistant leverages Gen AI to create various marketing and creative content, catering to businesses aiming to streamline content creation processes.

Beyond hype: Real-world applications of Gen AI

Gen AI is already making waves in various sectors:

  • Media and Entertainment: AI-generated music composes film scores and creates personalised soundtracks for video games. AI-written scripts streamline content creation for TV shows and advertisements.
  • Design and Fashion: AI generates unique clothing designs, product mockups, and personalised marketing materials. Architects leverage AI to explore innovative building concepts and optimise urban planning.
  • Science and Research: AI-powered drug discovery platforms accelerate the identification of promising drug candidates, while protein structure prediction tools aid in understanding diseases and developing targeted treatments.

Looking ahead: The future of Gen AI

As research and development continue, Gen AI’s capabilities will undoubtedly expand. Future advancements might include:

  • More personalised and interactive AI-generated content: Imagine AI tailoring music compositions to your mood or generating educational content that adapts to your learning style.
  • Enhanced automation of creative tasks: AI could design entire advertising campaigns, write novels, or even compose symphonies, pushing the boundaries of human creativity.
  • Integration with other AI technologies: Combining Gen AI with other AI advancements, like robotics and natural language processing, could lead to the creation of truly intelligent and interactive machines.

However, responsible development and deployment remain crucial. Addressing ethical concerns, establishing clear guidelines, and fostering public trust will be essential in ensuring Gen AI benefits society as a whole.

What do we think about Gen AI

Generative AI stands at a pivotal moment now more than ever to transform industries and redefine our creative landscape. Its potential to solve complex problems, automate tasks, and unleash boundless creativity is undeniable. 

While the ethical and societal implications of Gen AI is paramount, the ongoing research and development to push the boundaries of its capabilities, coupled with robust ethical frameworks and open dialogue to address potential risks can guide it in a monumental level.

Governments, companies, researchers, and the public must collaborate to ensure Gen AI is developed and used responsibly, serving as a tool for progress and empowerment rather than manipulation or harm.

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