Thomvest 的动态

In this insightful article in Business Insider, Ashish Kakran at Thomvest discusses the need for robust safeguards and controls with reporter Sri Muppidi when deploying large language models (LLMs). Startups like Opaque Systems are at the forefront of addressing these critical security threats, where there is a significant opportunity for innovators to assist with this critical need. #AI #Cybersecurity #LLMs #Innovation #Thomvest

AI thrives on data, but users are increasingly concerned about their privacy. How can startups navigate this delicate balance and develop solutions that respect user’s s data while leveraging the power of AI? It's a critical question in today's data-driven world. A recent report by the Pew Research Center found that 81% of Americans believe that the potential risks of companies collecting data about them outweigh the benefits. Startups have a unique opportunity to build trust by prioritizing data privacy from day one. ?????? ?????? ?? ?????????????? ??????????????? ???????? ?????? ???????? ??????????????'?? ???????????????????? ?????? ???????????????? ???????? ?????????????? ?????? ???????? ?????????????? ???????? ?????????? ????? ???????? ?????? ???????? ?????? ????????????????????????????: * ???????? ????????????????????????: Collect only the data you truly need for your AI model to function effectively. * ????????????????????????: Be upfront and clear about how you collect, store, and use user data. * ???????? ??????????????: Give users control over their data, including the ability to access, correct, or delete it. * ????????????????: Implement robust security measures to protect user data from unauthorized access or breaches. #AI #DataPrivacy #Startups #Ethics #TechForGood

Navigating the Challenges of Generative AI: A Comprehensive Guide to Security and Trust for Startups Generative AI startups are at the forefront of creating realistic and impactful digital content, but with this power comes the need for strong security measures to establish trust. For these companies, prioritizing a secure, ethical framework is essential to not only protect intellectual property but also to maintain the reliability of AI outputs. This guide covers critical steps for startups to ensure AI security and trustworthiness, focusing on data protection, model integrity, and alignment with ethical standards and regulations. Let’s explore how to build secure generative AI systems that inspire confidence and set the foundation for growth. read more: https://lnkd.in/gJdQNvfv #GenAI #Security #Startups #Privacy

AI and the Growing Concerns Around Data, Privacy, And Security ???? As AI continues to evolve, companies are exploring new paths to make it smarter and more capable. However, many AI specialists argue that longer training periods with more comprehensive datasets could lead to better results . The debate raises a critical question: What is the cost of rapid AI development, and how does it impact data gathering/usage, privacy, and security? The need for massive amounts of data to train AI comes with serious privacy and security concerns. The more data these models consume, the higher the risks of sensitive information being exposed or misused. Add to this the growing complexity of AI systems, and it’s clear we’re navigating uncharted territory where innovation, security, privacy, and ethical responsibility must go together. Organizations adopting AI must balance ambition with caution, ensuring that data privacy and security aren’t sacrificed in the race for better AI. The stakes are high, and the implications for businesses and individuals are enormous. The race for smarter AI should not come at the expense of individuals' and organizations' security and privacy. Balancing innovation with ethical responsibility a start for path forward but so much more is required. ????? #AI #privacy #datasecurity #ethicalAI #infosec #innovation #cybersecurity #data #dataprivacy #security #risk #hackers #attacksurface #freeze https://lnkd.in/egA4ZGu7

During my study, I noticed that... GenAI technologies hold great promise, but they also come with a range of risks that require careful attention. These risks can be grouped into two main categories: 1 – Data Risks Since GenAI systems are powered by vast amounts of data, they face significant risks related to how that data is handled. Key concerns include: a. Data leakage:– Sensitive information could be exposed or fall into the wrong hands. b. Privacy issues:– The misuse of personal data can violate privacy rights and erode trust. c. Compliance violations:– Failure to comply with regulations like GDPR can lead to legal and financial consequences. d. Bias:– Inaccurate or incomplete data can lead to biased results, which may reinforce unfair outcomes. e. Intellectual property loss:– Proprietary data could be misappropriated or exploited. 2 – Model Risks In addition to data risks, the AI models themselves present several potential threats, such as: a. Credibility and integrity loss:– If a model produces unreliable or misleading results, it can damage trust in the system. b. Malicious use:– Bad actors can misuse AI for harmful purposes, like spreading disinformation or launching cyberattacks. c. Security breaches:– AI models can be vulnerable to attacks that compromise their security or functionality. d. Data poisoning:– Malicious actors may manipulate the data used to train models, leading to skewed or harmful outcomes. e. Model stealing:– Competitors or hackers could copy or replicate AI models, leading to loss of intellectual property. f. Prompt injections:– Attackers might exploit vulnerabilities in prompts to manipulate model outputs. g. Malicious code injection:– Embedding harmful code into the model can create security risks or trigger unwanted behavior. Effectively managing these risks is crucial to ensure that GenAI technologies are used safely, responsibly, and in line with ethical standards. #isaca #genai #itaudit

*Protecting Against Shadow AI* In KalioTek's most recent blog article, we share a strategic approach to how venture-funded Life Science, AI & Technology companies can protect their businesses from the unintentional consequences of Shadow AI. Because KalioTek has witnessed the rapid expansion and use of easily accessible AI tools, many of which are being used by employees without proper approval or company oversight, we have incorporated key strategies to protect against this unwanted threat. KalioTek approaches this plan to include a combination of the following: ? Technology that provides secure levels of data protection ? Incorporating security standards & policies ? Education of leadership & employees Get the specific steps your company should consider to protect against Shadow AI here: https://lnkd.in/gufczhXf #ai #artificialintelligence #startups #lifesciences #ethicsai

AI/ML Regulations Are Here! Governments worldwide are rolling out new rules to govern AI/ML. Feeling overwhelmed by the new AI/ML regulations? AI and ML are revolutionizing industries, but with great power comes great responsibility.?Our users' data is sensitive, and we must protect it. Don't let data security and privacy concerns hold you back from innovation! Take your AI/ML journey to the next level with #Valueadd.? At ValueAdd, we're committed to ethical innovation, safeguarding your sensitive data through robust security measures at every stage, and ensuring data integrity and trust throughout the entire project lifecycle. . . . . Partner with Valueadd, connect with us at www.valueaddsofttech.com, and let's chat about your specific needs! #Technology #Tech #AI #ML #ArtificialIntelligence #MachineLearning #Ethics #DataEthics #DataSecurity #PrivacyMatters?#Privacy #CyberSecuirty #Security #Innovation #Transformation #TechEnterpreneurs #Business #Startups #DataScience #BigData #TechInnovation #ValueAdd #VAST

Security issues, unethical data scraping, and bias or discrimination are just a few of the consequences that we have seen stem from the use of AI... With AI innovation evolving rapidly, it’s important that organisations understand, monitor, and take key steps to mitigate these risks: ? Regular risk assessments – Implement regular risk assessments and ensure that all of the data that the AI model is being trained on, as well as the output, is correct and ethical. ? Follow ethical guidelines – Confirm that the AI model or bot that you are training or working with is following all relevant ethical guidelines in terms of data acquisition. ? Have robust data privacy measures – Put strict data privacy measures in place and ensure that they are being followed to avoid any data leaks or privacy breaches. ? Continuous monitoring – Continue to closely monitor the AI to ensure nothing goes awry and the content remains accurate and unbiased. ? Transparency in AI systems – Having a transparent AI system is a great way to make sure users understand how the model functions. ??Bias detection and mitigation – Implementing bias detection is one great way to ensure the AI is not producing discriminatory or inaccurate content. ? Clear accountability – Maintaining clear accountability is crucial when it comes to ensuring an AI model is well-respected and trusted. ? Compliance with regulations – Something that is vital when it comes to the use of AI is making sure that the model or bot is compliant with any and all applicable regulations. ? Adequate cybersecurity measures – Having good cybersecurity measures in place when working with an AI model is going to help protect private data, eliminating security issues further down the line. ? Regular updates and maintenance – AI models will often require regular updates and maintenance to run smoothly. This is something that can improve both the AI interface as well as the content it produces. AI is a powerful technology that can be of great use to organisations in many different fields. By understanding the risks and monitoring them, organisations are better equipped to mitigate the potential risks of AI. What does your organisation have in place to mitigate risks?

Just a glimpse of what’s coming as my partner Rama Sekhar, and #AI, supercharges our cybersecurity practice!