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AI demos can be misleading as real solutions take time

The artificial intelligence industry is filled with impressive demo videos featuring robots doing flips and AI applications responding like humans. However, these demos often do not reflect the challenges of real-world applications.

AI solutions require time to mature, especially within organizations, where learning from data is a lengthy process. Mistakes and setbacks are common, which can lead to disappointment.

While AI is expected to revolutionize industries, it’s crucial to remember that this transformation will take time.

In 2023, global investments in AI startups reached approximately $42.5 billion, with the United States leading with $67.2 billion, followed by China with $7.76 billion.

One of the key drivers attracting investors is the rapid advancement in generative AI. Investments in this area grew fivefold in 2023 compared to the previous year, with industry giants like OpenAI and Anthropic securing significant portions of the funds. OpenAI, for instance, received over $10 billion in investments.

Working under ideal conditions

AI demos typically operate under perfect conditions, showcasing the potential of systems. However, there is a significant gap between demos and real-world implementations.

Organizations often encounter challenges when trying to implement AI projects. These challenges make scaling and deploying AI solutions difficult. In 2023, 214 new AI unicorns – companies valued at over $1 billion – emerged, creating an additional $35 billion in value.

Sectors such as health care, finance and customer services are poised for significant transformations due to AI.

Data quality and management

For AI models to function effectively, they require vast amounts of high-quality data. However, organizations often face issues with incomplete, inconsistent, or poor-quality data.

Cleaning and organizing this data is time-consuming and costly, requiring organizations to make substantial investments. Moreover, data must be used in compliance with ethical and legal standards. AI projects also demand significant computing power and storage capacity, often relying heavily on cloud resources.

Workforce and training

Implementing AI projects requires a workforce skilled in data science, machine learning, and AI. Many organizations lack these competencies.

Retaining AI talent is challenging for many companies, and complying with legal regulations and industry-specific rules can slow down AI projects, especially in industries like health care, finance, and the public sector. Organizations must collaborate with legal and ethical experts to ensure compliance.

TT Ventures, the venture capital arm of Türk Telekom, has invested in global AI initiatives, including the AI company Cohere, through the Digital Transformation Capital Partners (DTCP) fund.

Cohere recently secured $450 million in funding, bringing its valuation to $5 billion.

TT Ventures’ General Manager Muhammed Özhan emphasized the company’s role in shaping the future by investing in global AI startups like Cohere, which is expected to bring technological innovation to Türkiye.

“Through Türk Telekom Ventures, we not only help move Turkish startups abroad but also play a key role in shaping the future by investing in groundbreaking global ventures. We closely follow global developments, particularly in transformative fields like generative AI, which is impacting the world,” said Özhan.

“One such investment is in Cohere, a company leading in this space. We are thrilled that Cohere’s innovations will contribute significantly to our country and the broader technology ecosystem.

Cultural and organizational resistance

As with any innovation, AI adoption often faces resistance. Typically, experts who are trying something for the first time are met with skepticism. Cultural resistance within organizations can make AI adoption challenging.

Employees may worry that AI will either take over their jobs or alter their roles. Therefore, institutions must emphasize that AI will complement human labor, and they should develop change management strategies to ease this transition.

AI applications, however, can make incorrect decisions or produce biased outcomes, making ethical responsibility and accountability crucial concerns. Organizations must ensure that AI systems operate ethically and transparently, and they should implement oversight processes to maintain control over these systems.

Scaling projects

While small-scale AI projects may perform well in demos, they often face scalability issues when applied to complex real-world processes.

Successfully scaling AI solutions across an entire organization requires careful planning and development of scalable technologies.

Research highlights challenges

Consulting firms and research organizations regularly publish studies on the challenges of AI implementation.

McKinsey’s annual report, titled The State of AI, explores how AI is being used in corporate environments and highlights key obstacles. This report also provides in-depth insights into scaling AI projects and integrating them into business processes.

Deloitte’s reports, particularly those from 2023, highlight the challenges faced during AI adoption and how to overcome them. Key focus areas include data management, workforce competencies, and compliance.

Similarly, Gartner’s “Hype Cycle for Artificial Intelligence, 2023” explores the maturity levels of AI technologies, addressing the challenges of implementing AI projects and the journey these technologies undergo to reach full maturity.

AI startup Novus secures $1.5M at $14M valuation

Istanbul and Boston-based artificial intelligence startup Novus has successfully closed its seed investment round, securing $1.5 million in funding.

Led by the Gelecek Etki Fund, managed in partnership with Vestel Ventures and Tacirler Portfolio Management, the round also saw participation from Sabancı Ventures, Inveo Ventures, DeBa and several international funds.

With the latest funding, Novus has reached a valuation of $14 million.

Novus has made significant strides in AI. The company previously graduated from prestigious programs such as NVIDIA Inception, MIT Sandbox, Google for Startups, and North America in 2022. That same year, it also secured investment from Startup Wise Guys at a valuation of $5 million.


Team members of AI startup Novus. (Courtesy of Novus)
Team members of AI startup Novus. (Courtesy of Novus)

The new funding round strengthens Novus’ position in the AI sector, allowing it to expand its reach and continue driving technological innovation.

Vorga Can, co-founder and chief revenue officer of Novus, said the collaboration with Turkish investors and business partners would greatly support the expansion of the company’s DOT product across the country.

“Additionally, we will continue offering on-prem solutions to BIST50-level corporate clients, while providing innovative technologies to SMEs and startups through our SaaS model,” said Can.

“This new funding round marks a significant step in our sustainable growth and innovation journey.”

Behavioral generative AI platform Quin secures nearly $2M funding

Quin AI, a behavioral generative artificial intelligence platform, has raised 1.5 million pounds ($1.97 million) in seed funding as the startup seeks to revolutionize online behavior prediction and personalization.

The round was led by Blackfinch Ventures, along with participation from SFC Capital, Logo Ventures and Finberg.

Quin AI provides innovative solutions for businesses looking to enhance customer experiences, increase website conversions and ultimately drive revenue.

By analyzing interactions with a company’s website or application, Quin AI accurately predicts customer behavior in real time, offering each customer a tailored experience.


Gonca and Gülşah Gülser, founders of Quin AI. (Courtesy of Quin AI)
Gonca and Gülşah Gülser, founders of Quin AI. (Courtesy of Quin AI)

Founded by sisters Gülşah and Gonca Gülser, the startup sets a new standard for privacy-focused AI solutions, concentrating solely on first-party data and current user actions.

Quin AI CEO Gülşah Gülser expressed excitement about securing support from such a distinguished group of investors who she says share the vision for the future of artificial intelligence.

“This investment will accelerate the development of our technology and enable businesses across various sectors to unlock the full potential of their online presence,” Gülser said.

OpenAI unveils new features at its first big tech showcase

ChatGPT-maker OpenAI hosted its first big technology showcase, bringing together hundreds of software developers and other attendees to unveil new features of its artificial intelligence tech.

The DevDay 2024 event marked OpenAI’s first annual developer conference to provide deeper insights into AI tools and technologies while fostering community engagement.

The company offered a new API that enables low-latency voice-to-voice applications, allowing users to create natural, real-time conversational experiences.

Additionally, GPT-4 has been fine-tuned to better process visual inputs, making it applicable in fields such as object recognition and medical imaging analysis.


The OpenAI logo is seen in this illustration taken May 20, 2024. (Reuters Photo)
The OpenAI logo is seen in this illustration taken May 20, 2024. (Reuters Photo)

Developers now have the ability to create and share their own GPT models, with the new GPT Store allowing these models to reach a broad audience and offer customizable solutions.

The newly launched API offers developers the opportunity to create smarter, action-oriented AI assistants that can execute code, retrieve information, and call functions, significantly speeding up software development and research processes.

To address potential copyright issues related to AI-generated content, OpenAI introduced the “Copyright Shield.” The program provides legal support for content created using OpenAI’s tools, offering a significant assurance for businesses in navigating intellectual property concerns.

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