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...

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

In the age of rapid technological advancements, deepfake technology has emerged as a double-edged sword. While it presents exciting possibilities for entertainment and creative expression, it also poses a significant threat to individuals and society as a whole. Deepfake fraud is the malicious use of manipulated audio and video content. It has the potential to undermine trust, compromise security, and wreak havoc on unsuspecting victims.

Deepfake fraud attempts have increased by 3000% this year. (Source)

In this comprehensive guide, we will explore deepfake fraud and effective strategies to protect ourselves against this emerging threat.

Read the entire article on the Typing Biometrics blog: https://typing.ai/blog/how-to-protect-against-deepfake-fraud

The rapid advancement of artificial intelligence (AI) has revolutionized various industries, but it has also introduced new risks. The fact is truer, particularly in the realm of cybersecurity. Hackers are increasingly leveraging AI to exploit vulnerabilities and launch sophisticated attacks on websites.

In this comprehensive guide, we will explore the potential threats posed by AI hacks and provide you with detailed strategies to protect your website against them.

Learn more about AI hacks.

Here are different types of AI hacks you should know:

Adversarial Attacks

Adversarial attacks involve manipulating AI models by injecting malicious data to deceive algorithms and generate false outcomes. These attacks exploit the vulnerabilities of AI algorithms to trick them into making incorrect decisions. Adversarial attacks can be used to bypass security measures, such as image recognition systems, spam filters, or even voice recognition systems.

AI-Generated Malware

Cybercriminals can develop AI-powered malware that adapts and evolves to avoid detection by traditional security measures. AI-generated malware can learn from its environment, modify its behavior, and even create new attack patterns, making it extremely difficult to detect and mitigate.

Read the entire article on the Protectumus website security blog: https://protectumus.com/blog/details/how-to-protec...

Introduction

In an era dominated by digital interactions, ensuring robust security measures is of paramount importance to safeguard sensitive information and maintain user trust in online platforms. Generative Artificial Intelligence (AI) has emerged as a transformative tool, offering innovative solutions to bolster security across various domains. Particularly in the realm of authentication and user identity verification, generative AI techniques like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) have opened up new avenues for building more reliable, sophisticated methods to verify user identities, detect fraud, and fortify cybersecurity.

The Power of Generative AI

Generative AI involves training models to produce content that mimics specific data distributions. GANs and VAEs, two prevalent types of generative models, have demonstrated exceptional capabilities in generating data that is virtually indistinguishable from genuine samples. This technology is now being harnessed to enhance security protocols in novel and effective ways, particularly in the domains of authentication and user identity verification.

Read the entire article on the Typing AI Biometrics blog: https://typing.ai/blog/enhancing-security-through-...

Biometric authentication offers improved convenience and security for users. The practice utilizes unique characteristics like facial recognition, fingerprints, voice authentication, typing biometrics (known as keystroke dynamics) etc., for user verification. Due to added convenience of biometric authentication, consumers are more willing to use this technology.

According to a survey, about 86% of its respondents are interested in using biometric authentication. In addition, about 70% of these respondents are more convenient and easier. (Source - https://www.authgear.com/post/biometric-authentica...)

You can read the entire article on the Typing Biometrics Blog: https://typing.ai/blog/why-use-biometric-authentication-in-2023

In the age of rapid technological advancements, the rise of digital interactions and transactions has brought about both convenience and risks. Cybercriminals are becoming increasingly sophisticated in their methods, necessitating the deployment of robust cybersecurity measures. Two critical aspects of this defense are KYC (Know Your Customer) verification and deepfake detection, which play pivotal roles in combating fraud and identity theft. Furthermore, the integration of biometric technologies further fortifies these defenses by providing enhanced authentication mechanisms. This article explores the importance of KYC verification, deepfake detection, and the utilization of biometrics in strengthening cybersecurity.

KYC Verification: Ensuring legitimate identities

KYC verification is an essential process employed by organizations to establish the identity and credibility of their customers. By verifying customers' identities, businesses can minimize the risk of fraud, money laundering, and terrorist financing. This process involves gathering relevant customer information, such as personal identification documents, proof of address, and other corroborating data.

Read the entire article on the Typing AI Biometrics blog: https://typing.ai/blog/the-vitality-of-kyc-verific...

At Typing AI Biometrics, we understand the significance of Environmental, Social, and Governance (ESG) factors in today's business landscape, especially as an AI cyber security startup. With the growing importance of ESG considerations in shaping investor decisions and corporate reputation, we are committed to integrating these principles into our operations and decision-making processes.

Environmental Responsibility

We believe that minimizing our environmental impact is crucial for long-term sustainability. As a result, we have implemented energy-efficient practices, reduced waste, and promoted sustainability within our organization. By taking proactive steps to limit our carbon footprint, we contribute to a greener future and foster a cleaner environment for generations to come.

Social Impact

Diversity and inclusion are fundamental values at Typing AI Biometrics. We strive to create a workplace that promotes equal opportunities for all employees, regardless of their background. By cultivating an inclusive environment, we harness the power of diverse perspectives and experiences, leading to innovative solutions and stronger team collaboration.

Governance and Security

Governance is a critical aspect of our business. We prioritize stringent security and privacy standards to protect our customers' data and maintain their trust. Our commitment to governance extends beyond regulatory compliance, as we continuously evaluate and enhance our internal policies and practices to align with industry best practices.

Read the entire article on the Typing AI Biometrics blog:
https://typing.ai/blog/prioritizing-esg-in-the-dna-of-typing-ai-biometrics-a-sustainable-and-responsible-future