GenAI in Computer Vision: A New Era of Creativity?
GenAI is a real scene-stealer. From Adobe’s Firefly Vector Model to Runway’s AI-generated people, spellbinding innovations are ushering in a new era of creativity.
The whacky and wonderful (and often alarming) AI-generated memes that populate newsfeeds are only the tip of a very large iceberg. With a global market value of $67.18 billion, GenAI is well-positioned to revolutionize the way the world works, including how we leverage existing technologies – Computer vision is a prime example.
Are we on the precipice of a creative revolution? Is GenAI-enabled computer vision the way to a more accessible, innovative future of design? Recent market growth would say a resounding YES!
Content Creation
Whether it’s de-aging Robert DeNiro or fueling algorithm-based synthetic photography, GenAI is rewriting the rulebook. Sometimes literally.
We may have seen it at the movies, but it’s worth remembering that GenAI-enabled computer vision isn’t confined to the silver screen. We’re watching it transform industries the world over, partly a result of it lowering the bar to entry.
GenAI has led to the democratization of content creation, opening up fresh possibilities for those trying to level the playing field in business. GenAI is granting easy access to high-quality content, regardless of expertise.
For business leaders, this provides a chance to reduce the costs of in-house content creation, increase their brand’s output, and automate tasks like scriptwriting, storyboarding, and content personalization.
Given the quality and accessibility of GenAI, it’s starting to look like those who aren’t using GenAI are risking losing out in 2024. IBM’s 2023 Global AI Adoption Index claims that 42% of IT professionals have used the tech, with 40% of businesses planning to explore it.
A Fragmented Funding Landscape
Despite the global dip in VC funding, the rate of GenAI investment has soared in the last few years, garnering $22.4bn in 2023, fueled by the OpenAI-Microsoft mega round of $10bn. 2024 looks set to follow suit, with the US taking the lion’s share of the overall GenAI market at $11.66bn (Statista).
A GenAI-enhanced world is proving difficult to navigate for many, with demand for computing power and memory rising. This has made space for yet more innovation, exemplified by Celestial AI’s Photonic Fabric, a platform that uses light to transfer data. Celestial AI secured a whopping $175 million in Series C funding in March.
That said, a slowing global economy combined with a tight talent market has led to a somewhat fragmented funding landscape, and businesses must work harder than ever to secure the right talent, funding, and partnerships.
GenAI is brimming with the promise of innovation, and it’s not all from the biggest names in business either (OpenAI, Gemini, etc.) – wonderful firms like Heygen, Pika, and Gridspace are pushing the boundaries across industries.
What’s causing the market movement? Our specialist Deep Tech recruiters have identified some key trends and challenges below.
Synthetic Data
Data is the lifeblood of computer vision. In a space where outcome quality depends on the depth and reliability of data sets, GenAI presents an interesting solution: Synthetic data.
The global synthetic data generation market is expected to see a 35% CAGR between 2023 and 2030, largely driven by the recent spike in data use cases. In North America, where you can find a staggering 72% of the world’s leading Deep Tech companies (68% of them in the US), opportunity is rife.
Synthetic data generation techniques like Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs) can alleviate the burden of laborious data collection and annotation, a critical bottleneck in many areas of computer vision.
Reduced Operational Costs
Budgets are getting leaner, talent is scarcer, and AI is more advanced than ever. The cost-saving ability represented by GenAI tools is an enticing prospect, bringing with it a renewed sense of productivity across a range of functions.
From customer service to design, the rise of AI-as-a-service is a force to be reckoned with, reducing the need for operational costs (chiefly, a human workforce) in the process.
Ethics and Explainability
In many ways, GenAI-enabled computer vision signifies a new era of transparency, explainability, and at the same time, confidentiality. How? More synthetic data!
Synthetic data generation allows for the creation of realistic training datasets without needing real-world information. This not only fosters transparency in the training processes (the data used to build the model is readily available for analysis), but it also mitigates the risk of bias in datasets, one of the largest stumbling blocks in today’s AI space.
Additionally, synthetic data can be manipulated to isolate specific variables, making the decision-making process of the computer vision model easier to understand – a key aspect of explainability.
Growing Demand for R&D
R&D departments have their virtual hands full nowadays. R&D processes are more expensive than ever, especially in areas like biopharma and healthcare. Thankfully, Advancements in computer vision and GenAI can drastically reduce these costs, and in cases like Pharma.AI, discover novel drug candidates.
A Bright Future
Innovators everywhere are in for a bright, GenAI-enhanced future, provided they can navigate the global talent troubles.
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