Mike Bruchanski, Chief Product Officer at HiddenLayer, brings over twenty years of expertise in product growth and engineering to the corporate. In his function, Bruchanski is accountable for shaping HiddenLayer’s product technique, overseeing the event pipeline, and driving innovation to help organizations adopting generative and predictive AI.
HiddenLayer is the main supplier of safety for AI. Its safety platform helps enterprises safeguard the machine studying fashions behind their most necessary merchandise. HiddenLayer is the one firm to supply turnkey safety for AI that doesn’t add pointless complexity to fashions and doesn’t require entry to uncooked information and algorithms. Based by a workforce with deep roots in safety and ML, HiddenLayer goals to guard enterprise AI from inference, bypass, extraction assaults, and mannequin theft.
You’ve had a powerful profession journey throughout product administration and AI safety. What impressed you to hitch HiddenLayer, and the way does this function align together with your private {and professional} targets?
I’ve at all times been drawn to fixing new and complicated issues, significantly the place cutting-edge know-how meets sensible software. Over the course of my profession, which has spanned aerospace, cybersecurity, and industrial automation, I’ve had the chance to pioneer progressive makes use of of AI and navigate the distinctive challenges that include it.
At HiddenLayer, these two worlds—AI innovation and safety—intersect in a approach that’s each essential and thrilling. I acknowledged that AI’s potential is transformative, however its vulnerabilities are sometimes underestimated. At HiddenLayer, I’m in a position to leverage my experience to guard this know-how whereas enabling organizations to deploy it confidently and responsibly. It’s the proper alignment of my technical background and fervour for driving impactful, scalable options.
What are probably the most important adversarial threats focusing on AI methods right this moment, and the way can organizations proactively mitigate these dangers?
The fast adoption of AI throughout industries has created new alternatives for cyber threats, very similar to we noticed with the rise of related gadgets. A few of these threats embody mannequin theft and inversion assaults, during which attackers extract delicate info or reverse-engineer AI fashions, doubtlessly exposing proprietary information or mental property.
To proactively deal with these dangers, organizations have to embed safety at each stage of the AI lifecycle. This contains making certain information integrity, safeguarding fashions in opposition to exploitation, and adopting options that target defending AI methods with out undermining their performance or efficiency. Safety should evolve alongside AI, and proactive measures right this moment are the perfect protection in opposition to tomorrow’s threats.
How does HiddenLayer’s strategy to AI safety differ from conventional cybersecurity strategies, and why is it significantly efficient for generative AI fashions?
Conventional cybersecurity strategies focus totally on securing networks and endpoints. HiddenLayer, nonetheless, takes a model-centric strategy, recognizing that AI methods themselves characterize a singular and invaluable assault floor. In contrast to typical approaches, HiddenLayer secures AI fashions instantly, addressing vulnerabilities like mannequin inversion, information poisoning, and adversarial manipulation. This focused safety ensures that the core asset—the AI itself—is safeguarded.
Moreover, HiddenLayer designs options tailor-made to real-world challenges. Our light-weight, non-invasive know-how integrates seamlessly into present workflows, making certain fashions stay protected with out compromising their efficiency. This strategy is especially efficient for generative AI fashions, which face heightened dangers akin to information leakage or unauthorized manipulation. By specializing in the AI itself, HiddenLayer units a brand new commonplace for securing the way forward for machine studying.
What are the most important challenges organizations face when integrating AI safety into their present cybersecurity infrastructure?
Organizations face a number of important challenges when making an attempt to combine AI safety into their present frameworks. First, many organizations wrestle with a data hole, as understanding the complexities of AI methods and their vulnerabilities requires specialised experience that isn’t at all times obtainable in-house. Second, there may be usually strain to undertake AI shortly to stay aggressive, however speeding to deploy options with out correct safety measures can result in long-term vulnerabilities. Lastly, balancing the necessity for strong safety with sustaining mannequin efficiency is a fragile problem. Organizations should be sure that any safety measures they implement don’t negatively influence the performance or accuracy of their AI methods.
To handle these challenges, organizations want a mixture of training, strategic planning, and entry to specialised instruments. HiddenLayer offers options that seamlessly combine safety into the AI lifecycle, enabling organizations to deal with innovation with out exposing themselves to pointless threat.
How does HiddenLayer guarantee its options stay light-weight and non-invasive whereas offering strong safety for AI fashions?
Our design philosophy prioritizes each effectiveness and operational simplicity. HiddenLayer’s options are API-driven, permitting for simple integration into present AI workflows with out important disruption. We deal with monitoring and defending AI fashions in actual time, avoiding alterations to their construction or efficiency.
Moreover, our know-how is designed to be environment friendly and scalable, functioning seamlessly throughout various environments, whether or not on-premises, within the cloud, or in hybrid setups. By adhering to those ideas, we be sure that our clients can safeguard their AI methods with out including pointless complexity to their operations.
How does HiddenLayer’s Automated Pink Teaming resolution streamline vulnerability testing for AI methods, and what industries have benefited most from this?
HiddenLayer’s Automated Pink Teaming leverages superior strategies to simulate real-world adversarial assaults on AI methods. This allows organizations to:
- Establish vulnerabilities early: By understanding how attackers would possibly goal their fashions, organizations can deal with weaknesses earlier than they’re exploited.
- Speed up testing cycles: Automation reduces the time and sources wanted for complete safety assessments.
- Adapt to evolving threats: Our resolution repeatedly updates to account for rising assault vectors.
Industries like finance, healthcare, manufacturing, protection, and important infrastructure—the place AI fashions deal with delicate information or drive important operations—have seen the best advantages. These sectors demand strong safety with out sacrificing reliability, making HiddenLayer’s strategy significantly impactful.
As Chief Product Officer, how do you foster a data-driven tradition in your product groups, and the way does that translate to raised safety options for purchasers?
At HiddenLayer, our product philosophy is rooted in three pillars:
- End result-oriented growth: We begin with the tip objective in thoughts, making certain that our merchandise ship tangible worth for purchasers.
- Information-driven decision-making: Feelings and opinions usually run excessive in startup environments. To chop by means of the noise, we depend on empirical proof to information our choices, monitoring every thing from product efficiency to market success.
- Holistic considering: We encourage groups to view the product lifecycle as a system, contemplating every thing from growth to advertising and gross sales.
By embedding these ideas, we’ve created a tradition that prioritizes relevance, effectiveness, and adaptableness. This not solely improves our product choices however ensures we’re persistently addressing the real-world safety challenges our clients face.
What recommendation would you give organizations hesitant to undertake AI resulting from safety issues?
For organizations cautious of adopting AI resulting from safety issues, it’s necessary to take a strategic and measured strategy. Start by constructing a powerful basis of safe information pipelines and strong governance practices to make sure information integrity and privateness. Begin small, piloting AI in particular, managed use instances the place it will probably ship measurable worth with out exposing essential methods. Leverage the experience of trusted companions to handle AI-specific safety wants and bridge inner data gaps. Lastly, steadiness innovation with warning by thoughtfully deploying AI to reap its advantages whereas managing potential dangers successfully. With the best preparation, organizations can confidently embrace AI with out compromising safety.
How does the latest U.S. Govt Order on AI Security and the EU AI Act affect HiddenLayer’s methods and product choices?
Latest laws just like the EU AI Act spotlight the rising emphasis on accountable AI deployment. At HiddenLayer, now we have proactively aligned our options to help compliance with these evolving requirements. Our instruments allow organizations to display adherence to AI security necessities by means of complete monitoring and reporting.
We additionally actively collaborate with regulatory our bodies to form business requirements and deal with the distinctive dangers related to AI. By staying forward of regulatory tendencies, we guarantee our clients can innovate responsibly and stay compliant in an more and more complicated panorama.
What gaps within the present AI safety panorama must be addressed urgently, and the way does HiddenLayer plan to sort out these?
The AI safety panorama faces two pressing gaps. First, AI fashions are invaluable property that must be shielded from theft, reverse engineering, and manipulation. HiddenLayer is main efforts to safe fashions in opposition to these threats by means of progressive options. Second, conventional safety instruments are sometimes ill-equipped to handle AI-specific vulnerabilities, creating a necessity for specialised risk detection capabilities.
To handle these challenges, HiddenLayer combines cutting-edge analysis with steady product evolution and market training. By specializing in mannequin safety and tailor-made risk detection, we goal to offer organizations with the instruments they should deploy AI securely and confidently.
Thanks for the nice interview, readers who want to study extra ought to go to HiddenLayer.
