ChatGPT is seeing increased use for search-style queries, but Google continues to dominate global search activity.

According to new data shared by SparkToro CEO Rand Fishkin, ChatGPT processes about 66 million search-intent prompts per day, while Google handles approximately 14 billion daily searches. That makes Google’s search volume more than 210 times greater.

Key figures:

• OpenAI CEO Sam Altman previously reported that ChatGPT handled 1 billion prompts per day in December 2023, rising to 2.5 billion by July 2024.
• A joint Harvard and OpenAI study estimated that 21.3% of prompts are “search-like”, leading to the current 66 million daily search-intent queries.
• Google processed 5 trillion searches in 2024, or about 14 billion per day.
• Estimates also suggest DuckDuckGo drives more referral traffic than ChatGPT.

Industry data indicates that AI-driven search accounts for less than 1% of web referrals, according to BrightEdge. Earlier this year, Fishkin noted that Google Search was approximately 373 times larger than ChatGPT.

Research from SparkToro and Datos suggests AI adoption does not reduce Google usage; in fact, users often increase their Google searches when adopting AI tools.

Outlook:
While AI-based discovery is expanding rapidly, the latest figures show that traditional search remains the dominant channel for online information and referral traffic.

HiFiles AI continues to evolve as a secure, intelligent chatbot platform designed for document-based knowledge extraction and conversational support. The most recent updates reflect a commitment to flexibility, security, and enterprise-grade control.

I. New functionality now available

1) Chat initialization without document upload
Users can now initiate new chat sessions without uploading a document. This enables broader applications, such as setting up chatbot logic before final documentation is prepared, or running generic assistants that aren’t bound to a specific file.

2) Custom domain and subdomain mapping
Chatbots can now be deployed under a domain or subdomain of the user’s choice. This supports branding and integration use cases where direct embedding is insufficient or where DNS-based identity is preferred.

A working example of this feature is visible at: https://iwashacked.com

3) Access control based on user registration status
HiFiles AI now supports access-level restrictions for bots based on whether an end-user is authenticated or anonymous. This capability is particularly valuable for gated resources, internal documentation, and any deployment where access segmentation is a compliance or policy requirement.

Read the entire article on the Typing AI Biometrics blog: https://typing.ai/blog/hifiles-ai-july-feature-upd...

Generative AI has transformed the way enterprises build, interact, and automate. But as adoption of large language models (LLMs) accelerates, so do the risks. From model manipulation to shadow usage, these systems introduce new and evolving threat vectors, many of which traditional security stacks fail to detect or mitigate effectively.

At Typing AI Biometrics, we combine behavioral biometrics with advanced AI security tooling to help organizations secure every layer of generative AI. Below, we outline the top 10 risks facing LLM-powered apps in 2025 and how to reduce exposure while maintaining innovation velocity.

1. Prompt Injection

Risk: Attackers craft inputs designed to manipulate model behavior, override safety constraints, or leak context data. These inputs may come from users or third-party systems.

Mitigation: Apply input validation and structure prompts using strict system/user separation. Monitor for anomalous patterns using behavioral AI. Deploy guardrails to detect and neutralize prompt manipulation before it reaches the model.

2. Data leakage through outputs

Risk: LLMs may expose internal data, personally identifiable information (PII), or confidential content unintentionally through completions.

Mitigation: Implement output filtering and redaction. Use behavioral identity signals to limit access to context-sensitive operations. Enforce context lifespan policies and log access trails.

3. Hallucinations

Risk: LLMs often generate plausible but false information, leading to poor decisions or compliance breaches when outputs are trusted too readily.

Mitigation: Integrate retrieval-augmented generation (RAG) with curated knowledge bases. Flag uncertain or unverifiable responses. Include human-in-the-loop (HITL) where business-critical accuracy is needed.

Read the entire article on the Typing AI Biometrics blog: https://typing.ai/blog/2025-top-10-risks-and-mitig...

As 2024 draws to a close, Typing AI Biometrics reflects on a year filled with innovation, collaboration, and major milestones. From groundbreaking partnerships to cutting-edge product launches, the company has strengthened its position as a leader in AI and biometric authentication.

1. Second year in the Google AI Startup Program - Scale Tier

In its second year as part of the prestigious Google AI Startup Program - Scale Tier, Typing AI Biometrics capitalized on the resources and support provided by Google. Key benefits included:

• Substantial cloud credits: The program offered up to $350,000 USD in Google Cloud and Firebase usage credits over two years. In the first year, credits totaled $250,000 USD, with 100% of Google Cloud expenses covered, including an additional $150,000 USD exclusively for AI startups. In the second year, 20% coverage of up to $100,000 USD was provided.
• Enhanced support: The company received $12,000 USD in Google Cloud Enhanced Support credits, ensuring access to expert technical assistance.
• Workspace productivity: Free access to Google Workspace Business Plus for 12 months streamlined communication and collaboration within the company.

These resources empowered Typing AI Biometrics to develop advanced cloud-based biometric solutions and enhance its operational efficiency.

2. Joining the MongoDB for Startups Program

In January 2024, Typing AI Biometrics joined the MongoDB for Startups program, further strengthening its technological infrastructure. Key benefits included:

• Database credits: $500 in MongoDB Atlas credits, with the potential for an additional $4,500 at the end of the first 12 months.
• Expert collaboration: Access to MongoDB experts for fast-tracked support, strategic partnerships, and joint go-to-market opportunities.
• Showcasing innovation: A platform to highlight Typing AI Biometrics’ AI solutions to MongoDB’s extensive user base, customers, and partners.

This partnership played a pivotal role in optimizing the company’s database operations, supporting its mission to revolutionize biometric authentication through AI-driven innovation.

3. Strategic Partnership with Kartaca

In June, Typing AI Biometrics announced a strategic collaboration with Kartaca, a technology consulting firm specializing in Google Cloud services. This partnership enabled Typing AI Biometrics to leverage Google's state-of-the-art AI tools, including:

• Gemini AI: For advanced natural language understanding and generative tasks.
• DialogFlow: To enhance conversational agents and streamline user interactions.
• Document AI: For automated document processing and data extraction.
• Vertex AI: To efficiently build, deploy, and scale machine learning models.

Read the entire article on the Typing AI blog: https://typing.ai/blog/typing-ai-biometrics-2024-y...

As 2024 draws to a close, Fil Rouge Capital (FRC) is celebrating a year filled with progress, partnerships, and accomplishments. The venture capital firm has once again proven its commitment to fostering innovation and empowering the next generation of startups.

Here’s a look at what made this year remarkable for Fil Rouge Capital:

Conversations That Spark Ideas

📊 1207 Meetings with Founders

FRC believes that great ideas start with meaningful conversations. This year’s founder meetings laid the foundation for exciting collaborations and groundbreaking ventures.

Building Connections Across Ecosystems

🗓️ 210 Events Attended

From conferences to pitch nights, Fil Rouge Capital stayed deeply engaged in the global startup ecosystem. These events strengthened relationships with founders, investors, and industry leaders, fueling innovation.

Uncovering Opportunities

📄 864 Pitch Decks Reviewed

The team diligently scouted for visionary founders and transformative ideas, ensuring their pipeline is brimming with potential game-changers.

Celebrating Successes

🚀 6 Successful Exits

This year marked significant milestones for portfolio companies achieving successful exits. These accomplishments underscore FRC’s dedication to nurturing businesses toward sustainable growth.

Exceptional Portfolio Performance

📈 115% Revenue Growth (YoY)

Visionary founders in the FRC portfolio delivered outstanding results, achieving an impressive year-over-year revenue increase.

Read the entire article on: The Startup Network

Biometric authentication is no longer a futuristic concept—it’s an integral part of our daily interactions with devices, systems, and services. As of 2024, fingerprint recognition, facial recognition, typing biometrics and voice authentication have become commonplace in consumer electronics, corporate security, and financial services.

But the landscape is rapidly evolving. By 2025, advances in hardware, software, and artificial intelligence (AI) are set to transform biometric authentication into a more secure, seamless, and privacy-centric experience.

1. Multimodal Biometric Systems

Traditional biometric systems rely on a single method, such as fingerprint or facial recognition. By 2025, multimodal biometric authentication will become the norm. These systems combine multiple biometric identifiers—like face, voice, palm veins, and gait analysis—into a unified security model. This shift is driven by the need for stronger security in response to increasingly sophisticated attack vectors like deepfakes and biometric spoofing.

Multimodal systems significantly reduce the probability of false acceptances and false rejections. They can adapt dynamically, choosing the optimal biometric method based on environmental conditions, user behavior, or device constraints. For example, if a user's face is obscured by a mask, the system may default to voice or gait recognition instead.

2. Privacy-Preserving Biometrics

A key focus for 2025 is privacy-preserving biometric authentication. Traditional biometric systems store raw biometric data (like fingerprint images) in centralized databases, which are vulnerable to breaches. The emerging approach is to use techniques like homomorphic encryption, secure multi-party computation (SMPC), and biometric template protection.

Read the entire article on the Typing Biometrics Blog: https://typing.ai/blog/the-evolution-of-biometric-...

The NIST Cybersecurity Framework 2.0, also known as NIST2, represents an important update to the original National Institute of Standards and Technology (NIST) framework, originally developed in 2014. Aimed primarily at helping organizations manage and mitigate cybersecurity risks, NIST2 brings new insights, additional guidance, and updates that reflect the rapidly changing landscape of cybersecurity threats and best practices.

Key Elements of NIST2

NIST2 retains the five core functions—Identify, Protect, Detect, Respond, and Recover—that provide a foundational approach to managing cybersecurity risk. However, it builds on these functions by adding more context and detailing practical applications, which allow organizations to better integrate cybersecurity across all business areas.

This version introduces a greater focus on resilience, urging organizations not only to prevent and detect cyber threats but also to build systems that can withstand and recover from attacks. This emphasis on resilience reflects the increasing number and sophistication of cyber threats and acknowledges that no organization is entirely immune from potential breaches.

Read the entire article on the Typing AI Biometrics blog: https://typing.ai/blog/the-nist-cybersecurity-framework-20

Cybersecurity threats changing quickly. More people working remotely. Businesses need digital identity verification solutions more than ever to use cloud services, and making online transactions. These solutions help confirm customer identities and keep sensitive information safe from unauthorized access.

New technologies like artificial intelligence, biometrics, and passwordless authentication are making security stronger. These advancements help businesses deal with ongoing cybersecurity challenges and build trust with their customers.

Importance of User Authentication

Good user authentication methods keep sensitive information safe and stop unauthorized access. It helps prevent identity theft and impersonation by verifying who users are. It ultimately helps in ensuring only the real owner can access their accounts.

Also, many industries have strict rules about data protection and privacy. Using strong authentication methods helps you follow these rules. It can keep you out of legal trouble and help you avoid fines.

Read the entire article on the Is it hacked blog: https://isithacked.com/blog/top-authentication-tre...

OWASP is a non-profit foundation focused on web application security. It offers freely accessible resources like forums, tools, videos, and documentation on their website. Their notable projects include the OWASP Top 10. It highlights web app security concerns. The OWASP API Security Top 10 identifies prevalent API security risks.

An Overview of Top 10 2024 OWASP API Security Risks

1) BOLA

Broken Object Level Authorization represents a critical vulnerability that comes from the failure to validate permissions of a user to execute a specific action on an object. It can potentially result in the unauthorized access, modification, or deletion of data.

According to OWASP this API security threat is widespread and exploitable. It is moderate in its business aspect and can be detected as well.

• It is essential to implement a robust authorization mechanism to mitigate this vulnerability.
• Developers should conduct thorough checks to validate actions of a user on individual records.

They should also perform comprehensive security tests prior to implementing any changes in a production environment. Organizations can significantly reduce the risk of BOLA vulnerabilities and safeguard sensitive data from unauthorized access and manipulation by following to these precautions.

2) Broken Authorization

This API security risk represents a significant security vulnerability that arises when an application's authentication endpoints are unable to identify attackers who are posing as someone else and subsequently grant them partial or complete access to the account.

It is crucial to have visibility and understanding of all potential authentication API endpoints to mitigate this vulnerability.

Read the entire article on the Typing AI Biometrics blog: https://typing.ai/blog/introduction-to-owasp-api-security-top-10-2024

AI has been making significant strides in recent years, particularly in the field of generative AI. Generative AI refers to machines and algorithms that can create new content. This new content includes images, text, and even music based on patterns and data.

One of the latest trends in generative AI is the emergence of Vertical AI. It promises to revolutionize how AI is applied in specific industries.

#genai #AI #artificialintelligence #Biometrics #typingbiometrics #generativeai #authentication #MFA #2FA

https://typing.ai/blog/vertical-ai-the-next-revolution-in-generative-ai