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Dyske Suematsu
Digital consultant, strategist, developer, writer, Martian
Dyske Suematsu is a seasoned digital consultant, strategist, developer, and writer with over 20 years of experience in the field of internet-based business growth.1 He is currently a Partner at CYCLE Interactive, a position he has held since October 2004.1
Professional Background
Dyske's expertise encompasses a wide range of digital services, including:
- Web design and development
- E-commerce
- Social media marketing
- Search engine optimization (SEO)
- Content creation
- Online advertising
- Podcasting
Education and Early Career
Dyske holds a BFA in Fine Arts from the School of Visual Arts and has also studied at The Juilliard School. His educational background in the arts has likely contributed to his ability to blend creativity with technical skills in his professional work.
Entrepreneurial Ventures
In addition to his role at CYCLE Interactive, Dyske has been involved in several other business ventures:
- Co-founder and CTO of GalaStream
- Founder of Pain in the English, a two-sided marketplace for proofreading and a discussion forum for English language topics, which he started in November 20021
CYCLE Interactive
At CYCLE Interactive, Dyske and his team specialize in creating digital products with high visual impact.1 The agency offers a comprehensive range of services, including:
- Website development
- App creation
- Advertising campaigns
- Digital video production
CYCLE Interactive prides itself on fusing art and engineering while managing the risks associated with cutting-edge technologies and creativity.1
Philosophy and Approach
Dyske describes himself as a "champion of small businesses and nonprofits".1 His approach involves:
- Emphasizing client communication
- Providing comprehensive solutions for businesses' internet needs
- Managing various aspects of internet presence on behalf of clients
Through his work, Dyske Suematsu continues to leverage his extensive experience and diverse skill set to help businesses grow and thrive in the digital landscape.
Highlights
The New York Times has a neat demonstration of AI "model collapse," where using AI-generated content to train future models leads to diminishing diversity and ultimately to complete homogeneity. For example, all digits of handwritten numbers converge into a blurry composite of all numbers, and AI-generated human faces merge into an average human face. To avoid this problem, AI companies must ensure that their training data is human-generated.
One positive aspect of this issue is that AI companies will need to pay for quality content. As we increasingly depend on AI to answer our questions, website traffic will likely decline since we won't need to verify sources for the vast majority of answers. Content creators won't have much incentive to share their work online if they cannot connect directly with their audience. Consequently, the quality of free content on the web may decline. However, I believe this is a problem that AI engineers can eventually solve. The real issue, I'd argue, is that "model collapse" was already happening in our brains long before ChatGPT was introduced.
AI mimics the way our brains work, so there is likely a real-life analog to every phenomenon we observe in AI. Feeding an AI-generated (or "interpreted") fact or idea to train another model is equivalent to relying entirely on articles written for laymen or political talking points to formulate our opinions and understanding without engaging with the source material.
In my experience, whenever social media erupts with anger over something someone said, almost without exception, the outraged individuals have never read the offending comment or idea in its original context, whether it's a court document, research paper, or hours-long interview. They simply echo the emotions expressed by the first person who interprets the comment. It's no surprise that the model (our way of understanding ideas/data) would collapse if everyone followed this pattern.
In politics, the first conservative to interpret any particular comment will shape the opinions of all the Red states, and the first liberal to interpret it will shape the opinions of all the Blue states. In fact, "talking points" are designed to achieve this effect most efficiently. We are deliberately causing models—our ways of understanding the world—to collapse into a few dominant perspectives.
In a two-party system like that of the US, this is a natural consequence because the party with greater diversity will always lose. Another factor is our reliance on emotions. We feel more secure and empowered when we agree with those around us. Holding a unique opinion can be anxiety-inducing. So, we are naturally wired for "model collapse."
What the New York Times' experiment reveals isn't just the danger of AI but also the vulnerabilities of our own brains. AI simply allows us to simulate the phenomenon and see the consequences in tangible forms. It's a lesson we need to apply to our own behavior.
#ai #artificialintelligence
In finding the love of your life, it is tempting to think you can filter candidates by certain criteria, such as a sense of humor, education, career, hobbies, music preferences, or movie choices. However, using the concept of machine learning, I will explain why this method of dating doesn’t work.
https://lnkd.in/exMGZyQ8
#ai #artificialintelligence #machinelearning #dating
