The art world traditionally feels impenetrable to outsiders, especially aspiring artists or collections. Galleries dominate the scene, intermediaries take unjust commissions, and access to the global market is reserved for a privileged few. Networked Artistic Learning Algorithm (NALA), a groundbreaking platform developed by MIT graduate and accomplished painter Ben Gulak, aims to address this gap.
NALA
Ben has combined his technical expertise with his artistic passion to change how art is discovered, sold, and appreciated, as he has observed how artists have been confined to local markets or reliant on gallery representation. With the shift to galleries selling online, artists can lose up to 65% of their earnings to middlemen between platform fees and gallery fees. This fragmented, opaque system prevents many talented creators from thriving and, at the same time, stifles creativity.
One of NALA’s most impactful features is its commission-free model, which ensures that artists retain 100% of their sales. In fact, during Miami’s Art Week, NALA hosted a booth at CONTEXT Miami, featuring a diverse roster of creators. NALA allowed participating artists to keep the full value of their sales, straying away from the approach of traditional galleries, which take significant commissions.
NALA is the fruit of Ben’s over two decades of experience in the art and tech worlds—a platform built by an artist for artists. It serves as a commission-free platform where artists can showcase their work, connect with buyers, and retain the full value of their sales.
Ben’s journey to creating NALA was eye-opening. He worked with emerging artists in Cuba early in his career, allowing him to gain profound insights. “I saw how geography could dictate an artist’s success,” Ben says. “One can buy a painting in Havana for $100 and sell the exact same work for $5,000 in London. The work hadn’t changed, but the market had. This disparity made me realize we need a system that gives artists direct access to buyers who value their work.”
With this experience, Ben decided to utilize the knowledge and expertise he gained and honed from his MIT studies in game theory and market dynamics to build a fairer, more transparent system. Ben’s dual identity as a painter and technology expert has earned him the respect of renowned figures in the industry, including Ollie Cox and King Saladeen, who have witnessed his contributions to art and innovation.
Ollie, the owner of London’s Graffik Gallery, recalls his first encounter with the NALA founder: “Ben’s work immediately stood out to me. His ability to combine pop culture with realism captured my attention. I knew he’d be a perfect fit alongside artists like Alec Monopoly and Banksy.”
King Saladeen (@kingsaladeen), a popular contemporary artist, echoes Ollie’s thoughts. He collaborated with Ben on a joint painting project that merged their distinct styles, producing works that captured the essence of both creators. “Having a tech background and a deep understanding of the art world is rare. With NALA, Ben’s solving real problems for artists on a global scale,” Saladeen states. These sentiments demonstrate Ben’s credibility as an artist and visionary technologist.
Ben developed NALA to operate through an advanced recommendation engine, which combines cutting-edge algorithms to create a personalized experience for every user. NALA recently launched its latest hybrid algorithm—a combination of its V2 and V3 models—balancing artist- and artwork-specific recommendations.
The V2 model operates under the assumption that creators typically produce cohesive collections. NALA identifies connections between artists with similar styles or themes by an artist’s portfolio through natural language processing (NLP). Users can then navigate a curated space of artists, where they encounter works from creators aligned with their preferences.
Meanwhile, the V3 model takes a more granular approach. It analyzes individual artworks using computer vision and deep learning algorithms. These tools extract detailed features such as composition, color palette, and thematic elements, allowing NALA to recommend pieces that align with a user’s unique visual and emotional preferences.
Combining these two models allows NALA to cater to users seeking to discover new artists and those looking for specific styles or themes. For example, a collector who shows a strong preference for abstract works might receive more artwork-specific suggestions. On the other hand, another interested in an artist’s broader portfolio might see more creator-focused recommendations. This adaptability ensures that NALA remains relevant and engaging for every user, continually refining its suggestions based on feedback.
For Ben, NALA is a movement set to reshape the art world. “Art has always been how we share our histories and stories,” he explains. “It’s a universal language that transcends borders. With NALA, I want to give every artist the opportunity to share their story with the world.” This desire stems from his belief that art should be accessible to all, both as a medium of expression and a means of connection. NALA eliminates traditional barriers, which means local artists can reach global audiences, facilitating a cross-cultural exchange that enriches creators and collectors.
NALA represents a bold reimagining of the art world. Ben, who blends advanced technology with an artist-centered ethos, positions the platform at the forefront of breaking down barriers, fostering inclusivity, and empowering creators to share their work on their terms.
