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AI Trends: Where We Are Now and What to Expect in the Future  

By Ryan Prete, Jun 15, 2023

Person in a dark shirt interacting with an advanced AI interface hologram, surrounded by technology and security icons, suggesting futuristic artificial intelligence applications.

Artificial Intelligence technology has made incredible strides since its first understandings as a futuristic improbability some decades ago. Even since the turn of the millennium, artificial intelligence, or AI, now encompasses capabilities that are shaping everyday life of all sectors and corners of the macroeconomic economy.     

What is the current state of AI?     

Artificial Intelligence has made major progress in recent years, with notable advancements across a wide array of fields, some including: 

1. Machine Learning:

This technology encompasses learning techniques, including image recognition, speech synthesis, natural language processing, autonomous vehicle technology, and much more. 

2. Computer Vision:   

This technology enables machines to understand and recognize videos and images. Capabilities range from facial recognition, self-driving car technology, transformer models, and more. 

3. Natural Language Processing (NLP):

NLP advancements have allowed for the development of chatbots, language translation tools, virtual assistants, and more, including the technology behind ChatGPT’s blockbuster model. 

4. AI in Industry: 

Artificial Intelligence has already been integrated into a myriad of industries including finance, retail, transportation, and manufacturing, allowing industries within these sectors to boost decision-making capabilities and optimize general operations. AI will soon be integrated into even more sectors and industries, which we will delve into below.

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While the future capabilities of artificial intelligence are hard to detail, here are a few potential examples of how experts believe AI will progress, it’s important to note that some of these properties are already being utilized in some forms. 

1. Creative and Generative AI:

This definition refers to AI’s ability to create new and orginal content which can exhibit artistic qualities: including, imagination, artistic qualities, and creativity. Some examples of what creative and generative AI can develop include: synthetic data, image creation, dataset reading, creative writing, news writing, and other written work.

2. AI Search Development:

This technology refers to the capabilities and techniques applied in the development of intelligent search systems which can retrieve crucial information from large swaths of data, in an effective and efficient way. Further, it refers to the application of AI algorithms and techniques which aim to enhance search engine technology. Some examples of AI Search Development capabilities include: Advancements in Natural Language Processing and Machine Learning, recommendation systems which analyze user behavior, historical data, and user interest, conversation search capabilities, and more. 


3. Automated Machine Learning (AutoML): 

AutoML encompasses the development and application of automated programs and tools which expedite the construction of machine learning models. AutoML’s mission is to allow users, who have little to no expertise in data science, the ability to build high-performing models. 


4. Computer Vision:

his subset of AI and computer science, devoted to the enablement of computers that extract relevant information and data from digital videos and photos; just as a human naturally does. The technology behind computer vision relies on image processing, pattern recognition, neural networks, deep learning, and more. Computer vision’s applications could become reliant on by multiple sectors, including healthcare, e-commerce, entertainment, robotics, surveillance, and more.  

5. AI in Cybersecurity:

As more corners of the globe become digital, the need for strengthened cybersecurity regimes become even more crucial for individuals, employers, governments, and healthcare data systems. AI could play a significant role in the advancement of cybersecurity systems by bolstering threat detection and prevention tools, user and entity behavior analytics—which can indicate potential insider threats, unauthorized access or compromised user accounts, and more—malware detection and analysis, fraud detection, vulnerability management, and additional capabilities. 

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6. AI in Healthcare:  

AI’s vast and unknown capabilities give it the potential to completely overhaul the healthcare industry, through elevations in patient care, treatment, medical research, and diagnosis processes. AI technologies could also allow for advancements in medical imaging—such as X-rays, CT scans, MRIs—which necessary to detect early stages of cancer, neurological disorders, and other serious illnesses. AI also has the potential to personalize patient prescriptions and medications, while managing healthcare corporations’ management and administration systems. Robotic-assisted surgeries, which are already in use in some scenarios, could offer needed procedures to populations which might not have the privilege of readily accessible healthcare.  


Where can I Invest in Up-and-Coming AI Startups? 

Well, through Linqto of course. We offer an array of exciting artificial intelligence companies, including our newest portfolio company addition,  

H2Oai., through its open-source machine learning automation platform, is working to revolutionize the world of AI. allows for users to experience the swift and effortless construction of AI models and applications, both in the cloud and on-premise. By partnering with, data scientists serving all sectors can access tools to boost productivity while deploying models both rapidly and cost effectively. is already at the forefront of the AI revolution, working with technology leaders like IBM, Microsoft, and Nvidia. also bolsters a rolodex of the nation’s largest companies, serving clients like Capital One, Progressive, Kaiser Permanente, and others seeking the most advanced forms of AI technology.  

Already sitting at a $1.6 billion valuation, has completed eight funding rounds, in turn securing over $250 million in funding from investors including Goldman Sachs, Pivot Investment Partners, Crane Venture Partners, Celesta Capital, and the Commonwealth Bank of Australia (CBA). 

Linqto also offers holdings in additional AI startups Standard AI, ASAPP, generative AI platform SambaNova, and complex artificial intelligence deep learning application developer Cerebras Systems. Current investors in these three AI startups include Temasek, GIC, BlackRock, Altimeter Capital, Benchmark Capital, Coatue Management, SK Networks, TI Platform Management, and many others. 

Why are firms investing in AI companies? 

The AI sector’s valuation has mushroomed over the past year, at a trailblazing pace never seen before. Statista currently value’s the AI sector at $100 billion, and expects that number to explode by twenty fold by 2030, placing its potential value at $2 trillion in under seven years. Venture capital firms completed nearly $240 billion in total deal value in 2022, according to VentureBeat, with that number expected to grow this year, venture capital firms are working to stock their war chests with as many AI companies as possible. Read more about VCs investing in AI

Even as we’ve delved deep into expectations surrounding AI’s future potential capabilities, limitless advancements could be ahead for the groundbreaking technology. Be sure to keep up on AI trends, startup news, and more by continuing to read Linqto’s original content. 

This material, provided by Linqto, is for informational purposes only and is not intended as investment advice or any form of professional guidance. Before making any investment decision, especially in the dynamic field of private markets, it is recommended that you seek advice from professional advisors. The information contained herein does not imply endorsement of any third parties or investment opportunities mentioned. Our market views and investment insights are subject to change and may not always reflect the most current developments. No assumption should be made regarding the profitability of any securities, sectors, or markets discussed. Past performance is not indicative of future results, and investing in private markets involves unique risks, including the potential for loss. Historical and hypothetical performance figures are provided to illustrate possible market behaviors and should not be relied upon as predictions of future performance.

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Ryan Prete

Ryan Prete

Ryan is a financial writer for Linqto, known for his original blog content, articles, and other works. He previously worked as a financial writer at PitchBook Data, where he covered private equity, and as a reporter for Bloomberg in Washington D.C.,where he reported on tax policy. Ryan has also reported on cybersecurity policy for Inside Washington Publishers. His work has been featured in The Wall Street Journal, Axios, Yahoo News, and Reuters. He is a graduate of the University of California, Santa Barbara.