By Sami Yaghma, Jun 15, 2023
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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, the AI industry has rapidly evolved and grown, encompassing capabilities that are shaping everyday life of all sectors and corners of the macroeconomic economy. Understanding what artificial intelligence is and why it matters is crucial to grasp the full scope of these advancements.
Artificial Intelligence has made major progress in recent years, with notable advancements across a wide array of fields, some including:
The acceleration of AI adoption in various sectors has brought about significant challenges, such as bias and fairness concerns. Keeping up with the latest AI trends is essential to understanding these developments.
This technology encompasses learning techniques, including image recognition, speech synthesis, natural language processing, autonomous vehicle technology, and much more. Addressing AI bias in machine learning products is crucial to ensure fair predictions and build trust.
This technology enables machines to understand and recognize videos and images. Capabilities range from facial recognition, self-driving car technology, transformer models, and more. The applications of AI in these fields have significant impacts on our daily lives.
NLP advancements have allowed for the development of chatbots, language translation tools, virtual assistants, and more, including the technology behind ChatGPT’s blockbuster model. Understanding how AI impacts the job market is crucial as NLP tools transform various industries.
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. Investing in AI has become increasingly attractive due to its transformative impact on these sectors. AI systems are being used in various industries, including healthcare and retail, to improve data quality and enhance operational efficiency.
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| AI Technology | Current State | Future Trends |
|---|---|---|
| Machine Learning | Image recognition, speech synthesis, NLP, autonomous vehicles | Improved bias and fairness, broader application across sectors |
| Computer Vision | Facial recognition, self-driving cars, image and video recognition | Enhanced healthcare diagnostics, e-commerce applications, robotics, surveillance |
| Natural Language Processing | Chatbots, language translation, virtual assistants | Advanced conversational agents, more accurate translation, better understanding of context |
| AI in Industry | Decision-making support, operational optimization in finance, retail, transportation, and manufacturing | Increased adoption in new sectors, more integrated decision-making tools |
| Creative and Generative AI | Content creation (text, images), synthetic data generation | synthetic data generation More sophisticated creative outputs, integration into various creative industries |
| AI Search Development | Intelligent search systems, recommendation systems | Enhanced search capabilities, better user personalization, conversational search |
| Automated Machine Learning | Tools for non-experts to build machine learning models | Greater accessibility for non-data scientists, faster model development cycles |
| AI in Cybersecurity | Threat detection and prevention, user behavior analytics, malware and fraud detection | Proactive anomaly detection, advanced threat intelligence, integration with global cybersecurity frameworks |
| AI in Healthcare | Medical imaging, patient care improvements, robotic-assisted surgeries | improvements, robotic-assisted surgeries Personalized medicine, early disease detection, more advanced robotic surgical procedures |
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. AI research encompasses a wide range of applications, including advancements in synthetic data and precision medicine. As AI expert Serg Masís notes, “The field seems to be mainly calming down – but it also feels like there’s some critical breakthroughs left and those will shake the industry” (Deci).
This definition refers to AI’s ability to create new and original 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. AI tools are also being used in creating art, graphic design, and other forms of creative content. As noted by Capgemini AI Research, “In 2024, generative AI might actually become useful for the regular, non-tech person, and we are going to see more people tinkering with a million little AI models” (Capgemini).
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.
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.
This subset of AI and computer science is 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 relied on by multiple sectors, including healthcare, e-commerce, entertainment, robotics, surveillance, and more. AI’s role in these industries is pivotal, especially in private equity where it drives innovative solutions. More details can be found in our analysis of artificial intelligence’s pivotal role in private equity.
As more corners of the globe become digital, the need for strengthened cybersecurity regimes becomes 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. Integrating AI into cybersecurity measures is essential for proactive detection of anomalies and new attack patterns.
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 are 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.
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Through Linqto’s secondary marketplace, our pre-IPO investment platform offers an array of exciting private artificial intelligence companies, including Anthropic, Shield AI, and H2O.ai.
H2O.ai, through its open-source machine learning automation platform, is working to revolutionize the world of AI. H2O.ai allows users to experience the swift and effortless construction of AI models and applications, both in the cloud and on-premise. By partnering with H2O.ai, data scientists serving all sectors can access tools to boost productivity while deploying models both rapidly and cost-effectively.
H2O.ai is already at the forefront of the AI revolution, working with technology leaders like IBM, Microsoft, and Nvidia. H2O.ai 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, H2O.ai 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 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.
The AI sector’s valuation has mushroomed over the past year, at a trailblazing pace never seen before. Statista currently values the AI sector at $100 billion and expects that number to explode 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.
Additionally, there are increasing global efforts to regulate AI, including the passing of specific AI laws in cities like New York City and actions taken by governments at both national and local levels. These regulations aim to ensure transparency, safety, and responsible practices, potentially impacting the development, use, and oversight of AI technology.
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. The rapid growth and evolution of the AI industry have led to record adoption, funding, and innovation in 2024. Key artificial intelligence trends to watch include computer vision, natural language generation, and robotic process automation, with groundbreaking projects triggering a generative AI craze and a resurgence in funding.
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.
Sami Yaghma
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