The hottest Technology Substack posts right now

And their main takeaways
Category
Top Technology Topics

Iran: Fake It Till You Make It

Seriously Risky Business • 0 implied HN points • 04 May 23
🕹 Technology Cybersecurity Legislation Data Breaches Tech news
  1. Iran is adopting a 'fake it till you make it' approach by combining cyber and influence operations.
  2. China's influence operations focus on promoting government narratives rather than amplifying cyber operations.
  3. The UK's National Cyber Force takes a more controlled and truthful approach to cyber operations, influencing people's actions through cognitive effects.

On Microsoft, Wyden's Bark May Have Some Bite

Seriously Risky Business • 0 implied HN points • 03 Aug 23
🕹 Technology Cybersecurity Data Privacy Internet Governance Cloud Computing
  1. Microsoft's lax security practices led to a hack, prompting a call for investigation by US government agencies.
  2. Recommendation to limit FBI's access to 702 data only for foreign intelligence purposes is supported.
  3. Cheerful news includes Azure's enhanced security features, Google's bug collision trend, and new supply chain analysis tools.

After Viasat, Space Systems Get Scrutiny

Seriously Risky Business • 0 implied HN points • 20 Apr 23
🕹 Technology Cyber Security International cooperation
  1. The US government is considering designating space systems as critical infrastructure due to increasing threats from adversarial nations.
  2. The US State Department is working on a cyber disaster relief program to help allies and partners recover from cyber attacks.
  3. International cyber security authorities are advocating for building products with 'Security-by-Design and Default' to enhance cybersecurity and reduce vulnerabilities.

Large Language Models Are Forcing Conversational AI Frameworks To Look Outward

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 14 Feb 23
🕹 Technology AI Machine Learning Natural Language Data science
  1. Conversational AI frameworks are increasingly adopting large language models (LLMs) to improve their capabilities, but this has made many of them very similar to each other.
  2. LLMs offer strong tools like generating training data and understanding multiple languages, which can enhance the way chatbots function.
  3. Despite their potential, LLMs face challenges such as the need for better fine-tuning and the risk of providing inaccurate information, which can impact their reliability.

Existing Rigid Chatbot Architecture Needs Large Language Model (LLM) Flexibility

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 15 Feb 23
🕹 Technology AI NLP Chatbots Frameworks
  1. Current chatbot systems are too rigid and are mostly based on fixed rules and flows. They can't adapt easily to different conversations, making them less effective.
  2. Large language models (LLMs) have the potential to make chatbots more flexible and smarter. They can help chatbots understand and respond to a wider range of user inputs.
  3. Innovative new frameworks for conversational AI are emerging. These allow for more personalized interactions by combining different components based on user needs.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

Biển Đông trên mạng

Thái | Hacker | Kỹ sư tin tặc • 0 implied HN points • 25 May 20
🕹 Technology Cybersecurity Hacking Internet
  1. The cyberspace is now a significant battlefield, where nations engage in cyber warfare to protect their interests beyond physical borders.
  2. China has been known to utilize hacker groups like Unit 61398 to conduct cyber espionage and theft of intellectual property from other countries.
  3. Vietnam has faced targeted cyber attacks, showcasing the importance of developing cybersecurity measures and fostering capabilities to defend national interests in the digital age.

Dùng Bluezone có nguy cơ lộ thông tin như thế nào?

Thái | Hacker | Kỹ sư tin tặc • 0 implied HN points • 28 Apr 20
🕹 Technology Security Privacy Mobile Apps Data Breach
  1. Bluezone's major security flaw is its use of a single fixed ID number for each user instead of changing codes like other tracing apps, posing risks of tracking and compromising personal information.
  2. To address this vulnerability, Bluezone should consider pausing the app, revamping the design using expertise from European and American specialists, and following established privacy-conscious tracing solution models.
  3. The privacy risks posed by Bluezone's current design can be mitigated by adopting safer solution methods prevalent in other parts of the world, potentially leading to increased user trust and adoption.

What Are Realistic GPT-4 Size Expectations?

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 15 Feb 23
🕹 Technology Artificial Intelligence Machine Learning Software Development Data science Natural Language Processing
  1. GPT-4 is likely to have around 1 trillion parameters, which is much smaller than the rumored 100 trillion. This is based on how language models have grown over time.
  2. Experts suggest that it's not just about the number of parameters. The quality of training data is equally important for improving performance in language models.
  3. There is a limited supply of high-quality language data. If better data sources don’t emerge, the growth of model sizes may slow down significantly.

Solving For The Long Tail Of Intent Distribution

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 16 Feb 23
🕹 Technology AI Chatbots Machine Learning Data science
  1. The long tail of intent distribution has a lot of important customer conversations that can be often overlooked. These conversations are key to understanding what users really want.
  2. Using existing customer data like conversation transcripts and reviews can help identify these overlooked intents. Analyzing this data properly allows for better understanding and response design.
  3. Aligning chatbot intents with actual customer conversations is crucial for success. This ensures that the chatbot effectively meets user needs and improves overall interaction.

The Anatomy Of Large Language Model (LLM) Powered Conversational Applications

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 17 Feb 23
🕹 Technology AI Machine Learning Software Development User Experience Natural Language
  1. To make applications using large language models (LLMs) successful, businesses need to ensure they add real value through their API calls.
  2. The development of a good framework is important for collaboration between designers and developers, helping to turn conversation designs smoothly into functional applications.
  3. User experience is key; users just want great experiences without worrying about the technology behind it.

Foundation Conversational AI Technologies Landscape

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 21 Feb 23
🕹 Technology AI NLP Chatbots Voicebots
  1. The conversational AI field is quickly evolving in three main areas: voicebots, agent assistance, and large language model (LLM) enablement.
  2. Many current AI systems focus on generating responses, but there's a missed opportunity to use predictive features effectively.
  3. Traditional natural language understanding systems still perform better in terms of cost and training compared to LLMs, especially for certain tasks.

Vietnam's contact tracing app broadcasting a fixed ID

Thái | Hacker | Kỹ sư tin tặc • 0 implied HN points • 26 Apr 20
🕹 Technology Contact Tracing Privacy Concerns Data security App Development
  1. Vietnam's contact tracing app, Bluezone, was found to be broadcasting a fixed 6-character ID, which poses serious risks by leaking user information.
  2. The fixed IDs generated by the app were predictable due to the method used, potentially leading to issues like denial of service attacks and high probability of ID collision.
  3. The app also stored sensitive information like observed IDs and Bluetooth device details in Android's public storage, allowing easy falsification of exposure records by users.

Truy vết người nhiễm bệnh

Thái | Hacker | Kỹ sư tin tặc • 0 implied HN points • 20 Apr 20
🕹 Technology Privacy Contact Tracing Data security Public Health
  1. Technology can help in contact tracing for diseases like Covid-19, easing the burden on manual tracing efforts.
  2. Bluetooth technology is considered more accurate for location tracking in contact tracing apps.
  3. Balancing privacy concerns with the need for effective contact tracing is a complex challenge that requires careful consideration.

Cảnh báo: lỗ hổng nghiêm trọng trong ứng dụng Bluezone

Thái | Hacker | Kỹ sư tin tặc • 0 implied HN points • 24 Apr 20
🕹 Technology Security Privacy Software Development Mobile Applications
  1. Bluezone app had serious security vulnerabilities that could compromise user safety and privacy.
  2. The unique ID system used in Bluezone could lead to tracking and exposure of sensitive information, raising concerns about user safety.
  3. The app's requirement for excessive permissions like access to location and storage without appropriate need raised red flags for user privacy.

Giải pháp truy vết tiếp xúc của BKAV

Thái | Hacker | Kỹ sư tin tặc • 0 implied HN points • 18 Apr 20
🕹 Technology Contact Tracing Cybersecurity Software Development Privacy Concerns Data Sharing
  1. BKAV announced a breakthrough contact tracing solution called Bluezone. It emphasizes privacy, selective proximity tracking, and global collaboration.
  2. Vietnam's approach of building upon existing solutions like DP3T is praised. Publishing technical documentation and addressing shortcomings are suggested for transparency and improvement.
  3. Encouragement is given for BKAV to participate in discussions and share their solution to showcase Vietnam's competency.

Chaining Large Language Model (LLM) Prompts Via Visual Programming

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 27 Feb 23
🕹 Technology Artificial Intelligence Programming Software Development Data science Product Design
  1. Chaining LLM prompts can make complex tasks easier to handle. It allows many prompts to work together for better results.
  2. Using templates for prompts helps to save time and keep things organized. They allow you to reuse parts of your prompts easily.
  3. There's a growing opportunity to combine traditional logic with LLMs. This mix can enhance chatbot and AI systems in powerful ways.

Thông báo: hội thảo mini về công nghệ truy vết đảm bảo riêng tư

Thái | Hacker | Kỹ sư tin tặc • 0 implied HN points • 18 Apr 20
🕹 Technology Privacy Contact Tracing Livestream Engineering COVID-19
  1. The event discusses privacy-preserving contact tracing technology and its potential impact on public health in dealing with COVID-19.
  2. The livestream features speakers from companies like Apple, Google, and Walmart Labs sharing insights on Bluetooth sensor engineering and the importance of contact tracing.
  3. Participants can interact with speakers by asking questions through the provided link or chatting directly on YouTube during the event.

The Introduction Of Chat Markup Language (ChatML) Is Important For A Number Of Reasons

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 02 Mar 23
🕹 Technology AI APIs NLP Data Software
  1. Chat Markup Language (ChatML) helps improve security for large language models by protecting against prompt injection attacks. This means it can make conversations safer and more reliable.
  2. ChatML organizes conversations into roles like system, assistant, and user. This helps clarify who is saying what in the conversation, which can reduce misunderstandings.
  3. The development of ChatML is just starting, and future updates will likely allow it to handle more than just text. It may soon include images, sound, and other data types, making it even more versatile.

Meta publicly released LLaMA (Large Language Model Meta AI)

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 01 Mar 23
🕹 Technology AI Machine Learning NLP Software Innovation
  1. Meta has released a new AI model called LLaMA, which is smaller and more efficient than previous models.
  2. Meta is being cautious about how they provide access to their models, unlike others like OpenAI.
  3. There is a growing demand for tools that help companies customize AI models for their specific needs.

Can The French Do It Better ? Tribe, Yellow, Zenly

Venture Prose • 0 implied HN points • 12 Oct 16
🕹 Technology Startups Apps Investments Entrepreneurs Tech Culture
  1. French apps Tribe, Yellow, and Zenly have attracted millions of downloads and hundreds of thousands of daily active users.
  2. These apps have shown resilience, starting as different products and evolving to their current successful versions with investor support.
  3. To truly succeed, these French apps still need to reach millions of daily active users with strong retention rates.

Our Brains Don’t Understand Artificial Intelligence

The Digital Anthropologist • 0 implied HN points • 11 Apr 23
🕹 Technology Artificial Intelligence Cultural impact Ethical Concerns Future implications
  1. Our brains struggle to truly comprehend Artificial Intelligence because we have anthropomorphized technology for so long, forming relationships and rituals around it.
  2. We evaluate new technologies based on personal and societal values, imagining how they will impact our future happiness and success individually and as a society.
  3. Despite the widespread concerns and excitement around AI, many of us are still uncertain about what it means for our future, especially in the midst of other global challenges.

Example Code & Implementation Considerations For GPT 3.5 Turbo, ChatML & Whisper

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 03 Mar 23
🕹 Technology AI Software Programming Data Security
  1. The GPT-3.5 Turbo model can produce different responses even with the same input because it is non-deterministic. This means you might not get the same answer every time you ask a question.
  2. To maintain context in conversations when using the API, you can use a few-shot approach by providing previous prompts and responses. This helps make the chat feel more natural.
  3. OpenAI's Whisper model can transcribe audio files and can even detect the language of the audio. It has good accuracy rates for several languages, with Spanish and Italian scoring the best.

When Using The ChatGPT API, Users Will Have To Manage The Context

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 06 Mar 23
🕹 Technology AI APIs NLP Chatbots Conversational AI
  1. When using the ChatGPT API, users must provide context for the conversation because it doesn't remember past interactions. You need to include previous messages to keep the conversation clear.
  2. If the number of messages exceeds a limit, you can keep only the most recent ones to save space. This way, the model still understands the flow of the conversation.
  3. If you want better responses, you should be clear with your instructions and specify what type of answer you need. Changing how you ask questions can help improve the output.

NLU & NLG Should Go Hand-In-Hand

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 07 Mar 23
🕹 Technology AI NLP Chatbots Software Data
  1. Using NLU and NLG together can make chatbots work better. They can detect what users want and give accurate responses.
  2. Traditional NLU systems still have strong abilities in understanding user intent that shouldn’t be ignored. They're a valuable asset in chatbot design.
  3. Regularly checking and updating the prompts used by chatbots can help improve how they respond to users, making interactions more effective.

The Tension in Specialization

Embracing Enigmas • 0 implied HN points • 12 Feb 24
🕹 Technology Machine Learning Models Specialization AI
  1. Specialization allows individuals to excel in a specific field but can limit performance in other areas.
  2. In nature, specialization is beneficial in specific environments, but changes over time can challenge specialized traits.
  3. Ensemble learning combines specialized models to cover each other's errors and excel in various contexts, emphasizing the importance of having both good and different models.

Join my new subscriber chat

Voohy Leadership Insights • 0 implied HN points • 13 Jul 24
🕹 Technology Apps Social media Communication Online Platforms User engagement
  1. There is a new chat space for subscribers to engage and discuss topics related to leadership. This chat allows for more direct interaction and conversation among members.
  2. To participate, subscribers need to download the Substack app and enable push notifications for live updates. This way, they won't miss out on any discussions.
  3. Joining the chat is easy; after downloading the app, subscribers can find the chat and jump in to say hello and participate in the discussions.

Adding A Moderation Layer To Your OpenAI Implementations

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 08 Mar 23
🕹 Technology AI API Moderation NLP Chatbots
  1. Adding a moderation layer to OpenAI implementations is essential to comply with usage policies. This helps avoid serious issues like account termination.
  2. The moderation endpoint is free to use and monitors for harmful content like hate, violence, and self-harm. Companies should check their API calls for inappropriate content.
  3. OpenAI is continually improving the moderation tools, but users need to frequently update their own policies to align with these changes. Regular checks can help ensure safe usage.

What Does ChatML Mean For Prompt Chaining Applications

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 09 Mar 23
🕹 Technology AI Data science Natural Language Software Development
  1. Chatbots allow users to input data more freely using natural language. This means people don't have to fit their input into specific forms or buttons.
  2. Prompt engineering helps users create effective prompts for large language models. It involves designing prompts that guide the model to produce the desired responses.
  3. With the introduction of ChatML, there will be a standard way to format prompts. This could make it easier for different applications to understand and process user requests.

Large Language Models, Foundation Models & Multi-Modal Models

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 13 Mar 23
🕹 Technology AI NLP Modeling Machine Learning Data science
  1. Large Language Models (LLMs) are being developed into Foundation Models that can handle tasks beyond just language, like images and voice. This shows how technology is evolving to be more versatile.
  2. GPT-4 is now seen as a Multi-Modal Model that combines different types of data, allowing it to work with text, images, and more. This expands the possibilities for AI applications.
  3. As the use of LLMs increases, there will be more focus on creating fine-tuned models. This means turning unstructured data into structured data for better interaction and understanding.

Three Ways In Which Whisper Is Advancing ChatGPT

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 14 Mar 23
🕹 Technology Artificial Intelligence Machine Learning Natural Language Processing Data science
  1. Speech to text has unique challenges, like disfluencies that happen when people talk. These differences can help improve how ChatGPT understands and processes voice input.
  2. Whisper can provide ChatGPT with access to lots of audio data. This means it can learn from a wider variety of information, which can make responses better.
  3. The future of AI models includes using different types of data, not just text. This shift towards multi-modal models means ChatGPT can eventually handle audio, images, and more, making it more versatile.

OpenAI Has Three New Use Modes, Each With Mode Specific Models

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 16 Mar 23
🕹 Technology AI Software Development Programming Machine Learning
  1. OpenAI has introduced three new modes for its language models. Each mode is designed for specific tasks like chat, insertion, and editing.
  2. These modes help users get better results by matching their tasks with the right model. Using the correct mode makes the AI work more effectively.
  3. Prompt engineering is now tailored to each mode. This means users will need to adjust their input templates to fit the specific needs of each mode.

Prompt Engineering, OpenAI & Modes

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 17 Mar 23
🕹 Technology AI NLP Chatbots Data Programming
  1. Prompt engineering is really important for getting the most out of large language models. Good prompts can help the model give accurate and relevant responses.
  2. To prevent models from making things up or 'hallucinating,' prompts need to be carefully structured and put together. This helps keep the context clear and the information reliable.
  3. OpenAI is working on improving the safety and quality of responses using better prompt structures. This reduces risks like prompt injection attacks and helps ensure more consistent answers.

Google Has Started To Open Access To Bard

Cobus Greyling on LLMs, NLU, NLP, chatbots & voicebots • 0 implied HN points • 22 Mar 23
🕹 Technology AI Software Development Innovation Online Services
  1. Google has opened access to Bard for users in the U.S. and U.K., with plans to expand to more places soon. You need to apply to access it.
  2. Bard is a helpful AI tool that gives users multiple answers to questions, letting them pick the best option. It works alongside Google Search to provide more information.
  3. Google designed Bard to be simple and efficient, aiming to use its search expertise to ensure users get reliable information and suggestions.

Announcement: Android Jetpack Security library

Thái | Hacker | Kỹ sư tin tặc • 0 implied HN points • 10 May 19
🕹 Technology Android Security Development Encryption APIs
  1. The Android Jetpack Security library provides APIs to easily encrypt files and shared preferences, enhancing data security for Android apps.
  2. The library offers a drop-in replacement for SharedPreferences and Editor classes, automatically encrypting/decrypting data to strengthen app security.
  3. Leveraging Android Keystore, the library ensures decryption of files or preferences only after user authentication, adding an extra layer of security to sensitive data.