Vectara is The Trusted GenAI Platform for All Builders - Retrieval Augmented Generation-as-a-Service (RAGaaS) to Power Your Busiiness - Put GenAI into Action. Vectara is an end-to-end platform for product builders to embed powerful generative AI features into their applications with extraordinary results. Built on a solid hybrid-search core, Vectara delivers the shortest path to a correct answer/action through a safe, secure, and trusted entry point. Vectara is a platform for companies with moderate to no AI experience that solves use cases, including conversational AI, question/answering, semantic app search, and research & analysis. Vectara provides an end-to-end SaaS solution abstracting the complex ML Operations pipeline (Extract, Encode, Index, Retrieve, Re-Rank, Summarize). Vectara is built for product managers and developers with an easily leveraged API that gives full access to the platform's powerful features. Vectara’s “Grounded Generation” allows businesses to quickly, safely, and affordably integrate best-in-class conversational AI and question-answering into their application with zero-shot precision. Vectara never trains on your data, allowing businesses to embed generative AI capabilities without the risk of data or privacy violations.

Vectara

Welcome to HackerNoon’s interview series. This section is curated by our Editorial team to spotlight bold and disruptive startups across the globe. If you’ve been nominated, and answer these questions Startups-Of-The-Year create a brand profile here. Hey Hackers, Vectara has been nominated in HackerNoon's annual Startup of the Year awards in Palo Alto, USA. Please : ]. vote for us here [https://hackernoon.com/startups/north-america/north-america-palo-alto-ca-usa#ljpyx4tp/ljpyx4tp Read more about us below to understand why we deserve your vote. Meet Vectara Vectara is an end-to-end platform for embedding powerful generative AI features into applications with extraordinary results. Built on a solid hybrid-search core, Vectara delivers the shortest path to a correct answer/action through a safe, secure, and trusted entry point. Vectara never trains on your data, allowing businesses to embed generative AI capabilities without the risk of data or privacy violations. My Role My name is Sean Anderson, and I am Head of Product Marketing at Vectara. I am excited to chat with developers daily who are making generative AI a reality. I want the world to know more about how Vectara solves the hallucination problem with LLMs and makes generative AI a reality for every business. How We're Disrupting/Improving the Generative AI Industry Companies need to act fast on their generative AI (Gen AI) strategies in response to ever-growing data volumes and the monumental shift in user expectations brought on by the advent of tools like ChatGPT. NLUs and large Language Models (LLMs) hold the promise of delivering business efficiencies, increasing profits, and decreasing costs. But Gen AI introduces operational complexities that need careful attention. CIOs, Product leads, and IT leaders find it hard to scale AI projects because they require deep ML expertise and maintenance of complicated LLMs, and even if they use open-source, the infrastructure is expensive to operate. There is a risk in assembling the components manually. The stakes run high because Gen AI also includes serious risks related to hallucination and data security. Enterprises that invest wisely in AI and LLMs will gain a competitive edge. Those who don’t will experience the costs, complications, and long lead times endemic to unwise DIY decisions. That competitive edge requires a proper workflow integration between internal data systems, existing solutions, expertise, and the right tools. Companies struggle to recruit, build, and implement next-generation generative AI techniques due to inexperience in data science and machine learning. The market is saturated with build-it-yourself LLM technology but many organizations can't adopt the risk and do not know where to start. Organizations need a safe entry point and end-to-end platforms to address the full spectrum of needs for Generative AI and hybrid search. Developers need to be able to easily embed Generative AI into their applications without the risk of exposing data (through sending off-site or being used as training data for the model). Standing Out From The Crowd Vectara provides an end-to-end SaaS solution abstracting the complex ML Operations pipeline (Extract, Encode, Index, Retrieve, Re-Rank, Summarize). Vectara’s “Grounded Generation” allows businesses to quickly, safely, and affordably integrate best-in-class conversational AI and question-answering into their application with zero-shot precision. Vectara never trains on your data, allowing businesses to embed generative AI capabilities without the risk of data or privacy violations. Vectara is built for product managers and developers with an easily leveraged API that gives full access to the platform's powerful features. Because Vectara indexes your own data, the risk of hallucination is all but eliminated, which is transferred and stored in encrypted form, and is never used to train Vectara models. Vectara is an end-to-end platform that handles indexing, encoding, evaluation, ranking, and summarization. Product developers can quickly build end-to-end generative solutions without maintaining and integrating individual components. Our Predictions/Thoughts on the Generative AI Industry in 2023 Since the launch of ChatGPT last year, the urgency around leveraging AI has never been greater. Many companies understand AI's value but don't fully understand the technology. Organizations seek trusted advisors to make their AI implementation successful and tools and platforms that simplify AI adoption by providing a safe entry point. These partnerships remove many barriers to adoption, including privacy and accuracy concerns. Companies struggle to recruit, build, and implement next-generation generative AI techniques due to inexperience in data science and machine learning. The market is saturated with build-it-yourself LLM technology, but many organizations can't adopt the risk and do not know where to start. Organizations need a safe entry point and end-to-end platforms to address the full spectrum of needs for Generative AI and hybrid search. Developers need to be able to easily embed Generative AI into their applications without the risk of exposing data (through sending off-site or being used as training data for the model). What word defines the state of Generative AI in 2023? At the beginning of 2023, the Vectara leadership team made some predictions of how AI will proliferate into our daily lives. Having experienced the explosion of generative AI and its feverish evolution, we know that time will continue to test these assumptions. Here are some areas we feel will advance the state of Generative AI in 2023. NLP will become so mainstream and part of everything we do, just like SW ate the world. The leaders in all segments will be applying NLP/LLM/GenerativeAI to jump their competition. The web will have its own layer of AI-powered additional information (similar to how we think about Augmented Reality); every major site will be layered with additional NLP-generated information, delivered based on user behavior. “Did you mean?”, “Check out these recommendations” and “Related Categories and Content” will become standard user interaction models in many more applications. AI-powered automation will begin to disrupt key software markets including document management, RPA, customer service, cybersecurity, legal contracts, and more. In 2 years, 80% or 90% of the world’s languages will be translated almost perfectly, allowing a regional language with few writers or speakers to be understood by someone else using a different regional language with few writers or speakers (the long tail) Why we decided to participate in HackerNoon's Startup of the Year awards We are excited and honored to participate in HackerNoon’s Startup of the Year awards and want to personally thank everyone who participates in the voting process for us and for startups in general. Vectara is a startup’s startup, founded by people like Amr, who started Cloudera and navigated through the emergence of big data and machine learning. The founders truly believe that AI can advance the state of our culture as long as the AI has all the relevance to make smart decisions. As a startup, we are uniquely positioned in the generative AI landscape to listen to our customers to shape our roadmap and features inside our platform. The HackerNoon Startup of the Year represents a stable of extremely talented startups, and our inclusion is a memorable milestone for the company. Today is another eventful day for us as we are launching our embedding model, Boomerang. We want to thank the HackerNoon community and everyone who took the time to vote for any startup. Final Thoughts 2023 very much feels like the year of emergence is generative AI. Encapsulating that interest with communities like the HackerNoon community and acknowledgment in these voting processes. Vectara is still a very young company in a fastly changing market. We look forward to working closely with early adopters of generative AI to understand the challenges they face. We are an open and inclusive community for developers of all experience levels. We invite you to continue the conversation with us here and on all our online platforms. [ ] Vote for us today! https://hackernoon.com/startups/north-america/north-america-palo-alto-ca-usa#ljpyx4tp/ljpyx4tp

Startups of the Year 2023: Vectara - The Platform for Embedding Powerful Generative AI Features

I started to summarize a dozen books by hand and found it was going to take me weeks for each summary. Then I remembered about this AI revolution happening and decided I was long past due to jump into these waters. . When I began exploring the use of large language models (LLM) for summarizing large texts, I found no clear direction on how to do so Some pages give example prompts to give GPT4 with the idea that it will magically know the contents of whatever book you want summarized. (NOT) Some people suggested i need to find a model with a large context that can process my whole text in one go. (Not Yet) Some open source tools are available that allow you to upload documents to a database and answer questions based on the contents of that database. (Getting Closer) Others have suggested that you must first divide the book into sections and feed them into the LLM for summarization one at a time. (Now we’re talking) Beyond that determination, there are numerous variables which must be accounted for when implementing a given LLM. I quickly realized, despite any recommendations or model rankings available, I was getting different results than what others have. Whether its my use-case, the model format, quantization, compression, prompt styles, or what? I don’t know. All I know is, do your own model rankings under your own working conditions. Don’t just believe some chart you read online. This guide provides some specifics into my process of determination and testing out the details of above mentioned variables. . Find the complete ranking data, walkthrough, and resulting summaries on GitHub Background Key Terms Some of these terms are used in different ways, depending on the context (no pun intended). : (AKA Model) A type of Artificial Intelligence that has  been trained upon massive datasets to understand and generate human language. Large Language Model (LLM) : OpenAI’s GPT3.5 and GPT4 which have taken the world by storm. (In our case we are choosing among open source and\or freely downloadable models found on .) Example Hugging Face : A technique, , of storing documents in a database that the LLM searches among to find an answer for a given user query (Document Q/A). Retrieval Augmented Generation (RAG) developed by Meta AI (AKA Prompt, or Context) is the query provided by the user. User Instructions: Example: “Summarize the following text : ” { text } Special instructions given before the user prompt, that helps shape the personality of your assistant. System Prompt: Example: “You are a helpful AI Assistant.” User instructions, and possibly a system prompt, and possibly previous rounds of question\answer pairs. (Previous Q/A pairs are also referred to simply as context). Context: : These are special character combinations that a LLM is trained with to recognize the difference between user instructions, system prompt and context from previous questions. Prompt Style Example: <s>[INST] {systemPrompt} [/INST] [INST] {previousQuestion} [/INST] {answer} </s> [INST] {userInstructions} [/INST] Indicates the number of parameters in a given model (higher is generally better). Parameters are the internal variables that the model learns during training and are used to make predictions. For my purposes, 7B models are likely to fit on a my GPU with 12GB VRAM. 7B: This is a specific format for LLM designed for consumer hardware (CPU/GPU). Whatever model you are interested in, for use in PrivateGPT, you must find its GGUF version (commonly made by ). GGUF: TheBloke When browsing the files of a GGUF repository you will see different versions of the same model. A higher number means less compressed, and better quality. The M in K_M means “Medium” and the S in K_S means “Small”. Q2-Q8 0, K_M or K_S: This is the memory capacity of your GPU. To load it completely to GPU, you will want a model smaller size than your available VRAM. VRAM: This is the metric LLM weighs language with. Each token consists of roughly 4 characters. Tokens: What is PrivateGPT? PrivateGPT (pgpt) is an that provides a user-interface and programmable API enabling users to use LLM with own hardware, at home. It allows you to upload documents to your own local database for RAG supported Document Q/A. open source project : PrivateGPT Documentation - Overview PrivateGPT provides an containing all the building blocks required to build . The API follows and extends OpenAI API standard, and supports both normal and streaming responses. That means that, if you can use OpenAI API in one of your tools, you can use your own PrivateGPT API instead, with no code changes, if you are running privateGPT in mode. API private, context-aware AI applications and for free local Overview I began by asking questions to book chapters, using the UI\RAG. PrivateGPT Then tried pre-selecting chunks of text for summarization. This inspired Round 1 rankings: Q/A vs Summarization. Next I wanted to find which models would do the best with this task, which led to Round 2 rankings, where was the clear winner. Mistral-7B-Instruct-v0.2 Then I wanted to get the best results from this model by ranking prompt styles, and writing code to get the exact prompt style expected. After that, of course, I had to test out various system prompts to see which would perform the best. Next, I tried a few, user prompts, to determine what is the exact best prompt to generate summaries that require the least post-processing, by me. Only once each model has been targeted to its most ideal conditions can they be properly ranked against each-other. Rankings When i began testing various LLM variants, came as part of PrivateGPT's default setup (made to run on your CPU). Here, I've preferred the Q8_0 variants. mistral-7b-instruct-v0.1.Q4_K_M.gguf While I've tried 50+ different Q8 GGUF for this same task, and haven’t found any better than . Mistral-7B-Instruct 0.2 Round 1 - Q/A vs Summary I quickly discovered when doing Q/A is that I get much better results when uploading smaller chunks of data into the database, and starting with a clean slate each time. So I began splitting PDF into chapters for Q/A purposes. For my first analysis I tested out 5 different LLM for the following tasks: Asking the same 30 questions to a 70 page book chapter. Summarizing that same 70 page book chapter, divided into 30 chunks. Question / Answer Ranking - My favorite, during these tests, but when actually editing the summaries I decided it was too verbose. Hermes Trismegistus Mistral 7b - Became my favorite of models tested in this round. SynthIA 7B V2 - Not as good as I’d like. Mistral 7b Instruct v0.1 Alot of filler and took the longest amount of time of them all. It scored a bit higher than mistral on quality\usefulness, but the amount of filler just made it less enjoyable to read. CollectiveCognition v1.1 Mistral 7b the answers were too short, and made its BS stand out a little more. A good model, but not for detailed book summaries. KAI 7b Instruct Shown, for each model Number of seconds required to generate the answer Sum of Subjective Usefulness\Quality Ratings How many characters were generated? Sum of context context chunks found in target range. Number of qualities listed below found in text generated: Filler (Extra words with less value) Short (Too short, not enough to work with.) BS (Not from this book and not helpful.) Good BS (Not from the targeted section but valid.) Model Rating Search Accuracy Characters Seconds BS Filler Short Good BS hermes-trismegistus-mistral-7b 68 56 62141 298 3 4 0 6 synthia-7b-v2.0 63 59 28087 188 1 7 7 0 mistral-7b-instruct-v0.1 51 56 21131 144 3 0 17 1 collectivecognition-v1.1-mistral-7b 56 57 59453 377 3 10 0 0 kai-7b-instruct 44 56 21480 117 5 0 18 0 Summary Ranking For this first round I split the chapter contents in to sections with a range of 900-14000 characters each (or 225-3500 tokens). NOTE: Despite the numerous large context models being released, for now, I still believe smaller context results in better summaries. I don’t prefer any more than 2750 tokens (11000 characters) per summarization task. - Still in the lead. It's verbose, with some filler. I can use these results. Hermes Trismegistus Mistral 7b - Pretty good, but too concise. Many of the answers were perfect, but 7 were too short\incomplete for use. SynthIA 7B - Just too short. Mistral 7b Instruct v0.1 - Just too short. KAI 7b Instruct - Lots of garbage. Some of the summaries were super detailed and perfect, but over half of the responses were a set of questions based on the text, not a summary. CollectiveCognition v1.1 Mistral 7b Not surprisingly, summaries performed much better than Q/A, since had a precisely targeted context. Name Score Characters Generated % Diff from OG Seconds to Generate Short Garbage BS Fill Questions Detailed hermes-trismegistus-mistral-7b 74 45870 -61 274 0 1 1 3 0 0 synthia-7b-v2.0 60 26849 -77 171 7 1 0 0 0 1 mistral-7b-instruct-v0.1 58 25797 -78 174 7 2 0 0 0 0 kai-7b-instruct 59 25057 -79 168 5 1 0 0 0 0 collectivecognition-v1.1-mistral-7b 31 29509 -75 214 0 1 1 2 17 8 Find the full data and rankings on or on GitHub: , . Google Docs QA Scores Summary Rankings Round 2: Summarization - Model Ranking Again, I prefer Q8 versions of 7B models. Finding that had been released was worth a new round of testing. Mistral 7b Instruct v0.2 I also decided to test the prompt style. PrivateGPT didn’t come packaged with the Mistral prompt, so I tried both of the defaults (llama2 and llama-index). - This model had become my favorite, so I used it as a benchmark. SynthIA-7B-v2.0-GGUF (Llama-index Prompt) Star of the show here, quite impressive. Mistral-7B-Instruct-v0.2 (Llama2 Prompt) Still good, but not good as using llama-index prompt Mistral-7B-Instruct-v0.2 as - Another by the same creator as Synthia v2. Good, but not good. Tess-7B-v1.4 as - worked ok, but slowly, with llama-index prompt. Just bad with llama2 prompt. (Should test again with Llama2 "Instruct Only" style) Llama-2-7B-32K-Instruct-GGUF Summary Ranking Only summaries, Q/A is just less efficient for book summarization. Model % Difference Score Comment Synthia 7b V2 -64.43790093 28 Good Mistral 7b Instruct v0.2 (Default Prompt) -60.81878508 33 VGood Mistral 7b Instruct v0.2 (Llama2 Prompt) -64.5871483 28 Good Tess 7b v1.4 -62.12938978 29 Less Structured Llama 2 7b 32k Instruct (Default) -61.39890553 27 Less Structured. Slow Find the full data and rankings on or on . Google Docs GitHub Round 3: Prompt Style In the previous round, I noticed was performing much better with default prompt than llama2. Mistral 7b Instruct v0.2 Well, actually, the mistral prompt is quite similar to llama2, but not exactly the same. llama_index (default) system: {{systemPrompt}}
user: {{userInstructions}}
assistant: {{assistantResponse}} llama2: <s> [INST] <<SYS>>
 {{systemPrompt}}
<</SYS>>

 {{userInstructions}} [/INST] mistral: <s>[INST] {{systemPrompt}} [/INST]</s>[INST] {{userInstructions}} [/INST] with the , then prompt styles. Next I went to work . I began testing output default llama2 coding the mistral template The results of that ranking gave me confidence that I coded correctly. Prompt Style % Difference Score Note Mistral -50% 51 Perfect! Default (llama-index) -42% 43 Bad headings Llama2 -47% 48 No Structure Find the full data and rankings on or on . Google Docs GitHub Round 4: System Prompts Once I got the prompt style dialed in, I tried a few different system prompts, and was surprised by the result! Name System Prompt Change Score Comment None -49.8 51 Perfect Default Prompt You are a helpful, respectful and honest assistant. \nAlways answer as helpfully as possible and follow ALL given instructions. \nDo not speculate or make up information. \nDo not reference any given instructions or context." -58.5 39 Less Nice MyPrompt1 "You are Loved. Act as an expert on summarization, outlining and structuring. \nYour style of writing should be informative and logical." -54.4 44 Less Nice Simple "You are a helpful AI assistant. Don't include any user instructions, or system context, as part of your output." -52.5 42 Less Nice In the end, I find that works best for my summaries without any system prompt. Mistral 7b Instruct v0.2 Maybe would have different results for a different task, or maybe better prompting, but this works good so I'm not messing with it. Find the full data and rankings on or on . Google Docs GitHub Round 5: User Prompt What I already began to suspect is that I’m getting better results with less words in the prompt. Since I found the best system prompt, for , I also tested which user prompt suits it best. Mistral 7b Instruct v0.2 Prompt vs OG score note Propmt0 Write concise, yet comprehensive, notes summarizing the following text. Use nested bullet points: with headings, terms, and key concepts in bold. Focus on essential knowledge from this text without adding any external information. 43% 11 Prompt1 Write concise, yet comprehensive, notes summarizing the following text. Use nested bullet points: with headings, terms, and key concepts in bold. Focus on essential knowledge from this text without adding any external information. 46% 11 Extra Notes Prompt2 Write comprehensive notes summarizing the following text. Use nested bullet points: with headings, terms, and key concepts in bold. 58% 15 Prompt3 Create concise bullet-point notes summarizing the important parts of the following text. Use nested bullet points, with headings terms and key concepts in bold, including whitespace to ensure readability. Avoid Repetition. 43% 10 Prompt4 Write concise notes summarizing the following text. Use nested bullet points: with headings, terms, and key concepts in bold. 41% 14 Prompt5 Create comprehensive, but concise, notes summarizing the following text. Use nested bullet points: with headings, terms, and key concepts in bold. 52% 14 Extra Notes Find the full data and rankings on or on . Google Docs GitHub Perhaps with more powerful hardware that can support 11b or 30b models I would get better results with more descriptive prompting. Even with Mistral 7b Instruct v0.2 I’m still open to trying some creative instructions, but for now I’m just happy to refine my existing process. Prompt2: Wins! Write comprehensive notes summarizing the following text. Use nested bullet points: with headings, terms, and key concepts in bold. In this case, comprehensive performs better than "concise", or even than "comprehensive, but concise". However, I do caution that this will depend on your use-case. What I'm looking for is a highly condensed and readable notes covering the important knowledge. Essentially, if I didn't read the original, I should still know what information it conveys, if not every specific detail. Even if I did read the original, I’m not going to remember the majority, later on. These notes are a quick reference to the main topics. Result Using knowledge gained from these tests, I summarized my first complete book, 539 pages in 5-6 hours!!! Incredible! Instead of spending weeks per summary, I completed my first 9 book summaries in only 10 days. Plagiarism You can see the results from below for each of the texts published, here. CopyLeaks Especially considering that this is not for profit, but for educational purposes, I believe these numbers are acceptable. Book Models Character Difference Identical Minor changes Paraphrased Total Matched Eastern Body Western Mind Synthia 7Bv2 -75% 3.5% 1.1% 0.8% 5.4% Healing Power Vagus Nerve Mistral-7B-Instruct-v0.2; SynthIA-7B-v2.0 -81% 1.2% 0.8% 2.5% 4.5% Ayurveda and the Mind Mistral-7B-Instruct-v0.2; SynthIA-7B-v2.0 -77% 0.5% 0.3% 1.2% 2% Healing the Fragmented Selves of Trauma Survivors Mistral-7B-Instruct-v0.2 -75% 2% A Secure Base Mistral-7B-Instruct-v0.2 -84% 0.3% 0.1% 0.3% 0.7% The Body Keeps the Score Mistral-7B-Instruct-v0.2 -74% 0.1% 0.2% 0.3% 0.5% Complete Book of Chakras Mistral-7B-Instruct-v0.2 -70% 0.3% 0.3% 0.4% 1.1% 50 Years of Attachment Theory Mistral-7B-Instruct-v0.2 -70% 1.1% 0.4% 2.1% 3.7% Attachment Disturbances in Adults Mistral-7B-Instruct-v0.2 -62% 1.1% 1.2% 0.7% 3.1% Psychology Major's Companion Mistral-7B-Instruct-v0.2 -62% 1.3% 1.2% 0.4% 2.9% Psychology in Your Life Mistral-7B-Instruct-v0.2 -74% 0.6% 0.4% 0.5% 1.6% Completed Book Summaries In parenthesis is the page count of the original. Instead of spending weeks per summary, I completed my first 9 book summaries in only 10 days. Anodea Judith (436 pages) Eastern Body Western Mind Stanley Rosenberg (335 Pages) Healing Power of the Vagus Nerve Dr. David Frawley (181 Pages) Ayurveda and the Mind Janina Fisher (367 Pages) Healing the Fragmented Selves of Trauma Survivors John Bowlby (133 Pages) A Secure Base Bessel van der Kolk (454 Pages) The Body Keeps the Score Steven Porges (37 pages) Yoga and Polyvagal Theory, from Polyvagal Safety Cynthia Dale (999 pages) Llewellyn's Complete Book of Chakras SECTION 1. CHAKRA FUNDAMENTALS AND BASIC PRACTICES s SECTION 2: CHAKRAS IN DEPTH. HISTORICAL, SCIENTIFIC, AND CROSS-CULTURAL UNDERSTANDINGS (54 pages) Fifty Years of Attachment Theory: The Donald Winnicott Memorial Lecture (477 Pages) Attachment Disturbances in Adults Dana S. Dunn, Jane S. Halonen (308 Pages) The Psychology Major's Companion (5 Pages) Walter Wink The Myth of Redemptive Violence Sarah Gison and Michael S. Gazzaniga (1072 Pages) Psychology In Your Life Walkthrough If you are interested to follow my steps more closely, check out the containing scripts and examples. walkthrough on GitHub, Conclusion Now that I have my processes refined, and feel confident working with prompt formats, I will conduct further tests. In fact, i already have conducted further tests and rankings (will publish those next), but of course will do more tests again and continue learning! I still believe if you want to get the best results for whatever task you perform with AI, you ought to run your own experiments and see what works best. Don’t rely solely on popular model rankings, but use them to guide your own research. Additional Resources ( ) Pressure-tested the most popular open-source LLMs (Large Language Models) for their Long Context Recall abilities u/ramprasad27 Part 2 / - 💢 Pressure testing the context window of open LLMs LeonEricsson llmcontext Chatbox Arena Leaderboard u/WolframRavenwolf 🐺🐦‍⬛ LLM Comparison/Test: Ranking updated with 10 new models (the best 7Bs)! u/WolframRavenwolf 🐺🐦‍⬛ LLM Prompt Format Comparison/Test: Mixtral 8x7B Instruct with 17 different instruct templates Vectara Hallucination leaderboard Also appears . here

PrivateGPT for Book Summarization: Testing and Ranking Configuration Variables

বই সংক্ষিপ্তকরণের জন্য ব্যক্তিগত জিপিটি: টেস্টিং এবং র‌্যাঙ্কিং কনফিগারেশন ভেরিয়েবল

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PrivateGPT para resumen de libros: variables de configuración de prueba y clasificación

PrivateGPT pour la synthèse de livres : variables de configuration de test et de classement

पुस्तक सारांश के लिए PrivateGPT: परीक्षण और रैंकिंग कॉन्फ़िगरेशन चर

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도서 요약을 위한 PrivateGPT: 구성 변수 테스트 및 순위 지정

PrivateGPT para resumo de livros: teste e classificação de variáveis de configuração

PrivateGPT для обобщения книг: тестирование и ранжирование переменных конфигурации

Kitap Özetleme için PrivateGPT: Yapılandırma Değişkenlerini Test Etme ve Sıralama

PrivateGPT dành cho tóm tắt sách: Kiểm tra và xếp hạng các biến cấu hình

用于书籍摘要的 PrivateGPT：测试和排名配置变量

Breaches and cyber attacks dominate headlines today. Hardly a week goes by without news of another massive data leak or ransomware attack bringing a company to its knees. In fact, studies show that the of organizations have experienced cyberattacks. As threats proliferate, organizations invest heavily in security tools and staff. large majority The average enterprise uses a ridiculous and technologies. More tools mean more alerts and more alerts lead to alert fatigue. Unsurprisingly, a found that too many tools decrease effectiveness, hindering cybersecurity efforts. Exhausted security teams struggle to separate signal from noise, leading to missed threats and breaches. 45 different security solutions survey This rising tide of alerts threatens to drown security teams. A found that security analysts can’t deal with 67% of the daily alerts they receive. Most alerts are false positives and not worth the time. study by Vectra AI New cybersecurity vendors like Kivera are pioneering preventative approaches to cloud security. Rather than just detecting threats, before they happen to reduce the number of alerts in the first place. This prevents issues upfront rather than reacting after the fact. Kivera stops misconfigurations The Root Cause of Most Cloud Breaches The root cause behind most cloud breaches is misconfigured resources and permissions. Research suggests will result from customer misconfigurations by 2025. Cloud environments are incredibly complex, with thousands of services and configuration options. Just one mistake can leave an opening for attackers to exploit. 99% of cloud security failures All those misconfigured cloud resources trigger floods of policy violation alerts. But detecting problems after they occur is too late. The damage is already done. Attackers move quickly to take advantage of any slip-up. By the time an alert is triggered, sensitive data may have already been stolen. That's why forward-thinking organizations are shifting to preventative security controls. The traditional reactive model of detect-alert-respond is simply unsustainable. Prevention stops mistakes and policy violations before they ever happen. The Limitations of Detection-Focused Tools Cloud-native security tools on the market today focus heavily on detection and response. These tools are valuable layers of defense but come with inherent limitations: Cloud security posture management (CSPM) solutions from vendors such as Wiz and Orca continuously monitor cloud configurations and permissions. They identify resources that violate security policies or best practices. But again, problems are only detected after misconfigurations occur. The latest evolution in cloud security is cloud-native application protection platforms (CNAPP). Companies like Sysdig and Palo Alto Networks provide CNAPPs that combine security tools such as CSPM and CWPP with code scanning for cloud security. While these platforms embed security in code and templates, they face limitations in infrastructure-as-code scanning, restricted to specific programming languages. Kivera overcomes this by operating at the API level, offering a more universal and adaptable security solution.\ However, CNAPPs still rely heavily on threat detection and response. They aim to identify anomalies in cloud applications and resources. However, gaps that allow the attacks in the first place are not directly addressed. The Preventative Security Model The limitations of these detection-focused tools highlight the need for a preventative approach to cloud security. The ideal security model employs a mix of preventative and detective controls, commonly referred to as the “layered security model.” Preventative controls stop policy violations and misconfigurations before they happen. Rather than reacting to events, preventative controls proactively enforce security requirements within systems. Prevention provides a first line of defense to maintain a strong security posture. Detective controls then provide a second line of defense to identify threats that make it past the preventative line. Detective controls are still vital for monitoring, investigation, and incident response. Historically, implementing detective controls in a preventive manner has been challenging, but new tools provide an effective solution to enforce these common detective controls preventively, enhancing overall security posture. Why We Need Preventative Cloud Security This is where preventative approaches to cloud security become essential. Adopting such methods involves deploying inline security measures between users and the cloud. As deployment requests are made, these security systems analyze them against configured security policies. Any requests that violate these policies are immediately blocked, ensuring that only compliant resources are created. This approach emphasizes prevention over detection, eliminating the flood of policy violation alerts by avoiding misconfigurations in the first place. Security teams can then concentrate on real incidents rather than addressing misconfiguration. Vendors like are at the forefront in this area of cloud security. Kivera's solution allows customers to define flexible guardrails and policies tailored to their organization's needs. It then enforces these policies in real-time as users interact with the cloud, preventing misconfigurations at their source and avoiding reactionary measures after the fact. Kivera Best practices for implementing a prevent-first strategy include phasing in prevention by starting with the highest-risk misconfiguration threats and then incrementally expanding policies. Prevention should also be combined with detection tools for layered defenses to catch novel threats while tuning alerting to focus only on critical issues not prevented outright. Processes and training must align with prevention, emphasizing configuring policies over correcting violations. And any violations that still occur should be regularly reviewed to identify and address gaps in coverage. The Future of Cloud Security Today's cloud-first world demands a new approach to security. The volume and pace of threats have rendered traditional reactive models ineffective. Organizations need to prevent threats upfront before damage occurs. The future of security is prevention combined with detection. Organizations still need layered defenses to catch evolving threats. But prevention must come first to establish a robust security posture.

The Missing Piece in Cybersecurity: Tools that Go Beyond Issue Detection

Data Management and Consolidation in the Integration of Corporate Information Systems

Picture this: a boardroom filled with skeptical executives, unsure of whether to give their precious budget to yet another salesperson. Suddenly, you whip out your tablet, point it at a seemingly ordinary product sitting on a table, and like magic, it springs to life before their very eyes. The once-static object transforms into a dynamic and interactive 3D model, revealing its inner workings, features, and potential applications. The audience is left dumbfounded, jaws dropped, their wallets trembling with anticipation. In a world where supply chain sales can be as dry as the Sahara, augmented reality is a breath of fresh air in the industry. Today, I will teach you step by step how to use Augmented reality to pitch your next consumer product, so strap yourselves in and prepare to be amazed. Step 1: Identify the needs of your buyers/customers In the realm of consumer product creation, the journey begins with identifying the very heartbeat of success: customer needs (or buyers' needs, in our case). To identify customer needs, you must first immerse yourself in their world. Cultivate empathy and actively listen to their desires, challenges, and feedback. Engage in conversations, conduct surveys, and explore social media platforms to gain insights into their preferences, pain points, and aspirations. Observe their daily routines, frustrations, and unmet desires. By understanding their world, you will lay a strong foundation for creating a product that truly addresses their needs. Step 2: Identify your product features and characteristics Now that you’ve identified what product you want to create (and why!) it is time to draft your product specifications. Start by identifying the key features and functions that will make your product stand out. Brainstorm a comprehensive list of desired capabilities, considering both the essential and desirable aspects. Prioritize these features based on their importance to the overall user experience and the value they bring to your target audience. Specify the performance and quality standards that your product must meet. Consider factors such as durability, reliability, efficiency, and safety. Define any industry-specific certifications or regulatory requirements that apply to your product. Ensure that the specifications reflect the desired level of performance and quality you want to deliver to your customers. Next, outline the physical and technical attributes of your product. This includes dimensions, weight, materials, PMS colors, interfaces, connectivity options, and any other relevant physical or technical specifications. Be as precise and detailed as possible, as these attributes will guide the design and manufacturing processes. Step 3: Create a 3D mockup of your product Armed with your product specifications, it is now time to take a huge step towards providing the Augmented Reality experience that will make you stand out, by creating a 3D model of your product. At that stage, if you’re not a 3D designer, I would recommend hiring one, as it takes years of experience to be proficient in that space. However, for the sake of documentation, here is an outline of the process that is required to create a 3D mockup. Selecting the appropriate software is paramount to creating a 3D mockup. There are several options available, ranging from professional CAD software to user-friendly design tools. Evaluate your requirements, budget, and proficiency level to find the software that best suits your needs. Popular options include SolidWorks, AutoCAD, Blender, and SketchUp. To create an accurate and detailed 3D mockup, gather reference material for your object. Collect photographs, technical drawings, and any other visual references that will aid in recreating its form and proportions. Pay attention to intricate details, textures, and surfaces that contribute to the object's overall appearance. With your concept and reference material in hand, it's time to start modeling. Begin by creating a basic shape or outline of your object using the software's modeling tools. Extrude, scale, and rotate the basic shapes to build the foundation of your 3D mockup. As you progress, refine the details, adding edges, curves, and other features that mimic the real-world object. To enhance the realism of your 3D mockup, apply textures and materials to its surfaces. Utilize the software's material libraries or create custom textures to mimic the appearance of the object. Experiment with different finishes, colors, and materials to achieve the desired visual representation. This step adds depth and visual appeal to your mockup. Lighting plays a crucial role in creating a realistic 3D mockup. Set up virtual lights within the software to illuminate the object from various angles, mimicking real-world lighting conditions. Experiment with different lighting setups to highlight specific features and create a visually appealing presentation. Once the lighting is set, initiate the rendering process to generate high-quality images or animations of your 3D mockup. Finally, review your mockup from different angles, evaluate its form and functionality, and seek feedback from colleagues or potential users. Make necessary adjustments and refinements to improve the accuracy and realism of your design. Repeat this process until you are satisfied with the final result. Step 4: Convert your 3D mockup to an Augmented Reality experience Just a heads-up before diving into that part; I don’t work for Vectary, nor am I sponsored, but I found it the best and most cost-effective tool to convert a 3D object into an Augmented Reality experience. So first, ensure that your 3D object is properly exported. Make sure it is in a compatible file format, such as OBJ, GLTF, or FBX. Check the geometry, textures, and materials to ensure they are optimized for AR rendering. If needed, clean up the model, optimize the polygon count, and apply appropriate UV mapping for texturing. If you haven't already, sign up for a Vectary account to access its AR features. Once logged in, import your 3D object into the Vectary editor. Simply drag and drop the file or use the import function to bring your 3D object into the Vectary workspace. Go to the properties menu and under advanced settings add Augmented reality. The AR file will be generated automatically. Once this is done, go back and unhide all the previously hidden objects. Share the project using the button in the top right corner. Then, on a mobile device, just press the AR icon to display it. Once you have created your AR experience, it's essential to test and preview it before sharing it with others. Vectary allows you to preview the AR scene directly in the editor using your device's camera. This feature enables you to visualize how the 3D object will appear and behave in the real world. Make any necessary adjustments or refinements based on your preview experience. . Here is a link to a video demonstrating the process Step 5: Time to pitch. You can take it from there, but below is the final result that we send to our buyers, at City Global. Conclusion A few years ago, you had to rely on 2D or 3D imagery in order to convince a buyer to allocate you some of its budgets. Today, Augmented Reality empowers you to demonstrate how a product is going to look in its environment, without having to go through a lengthy prototyping process. Moreover, recent advancements in technology made AR cost and time efficient, and we can foresee a future where AR won’t be an innovation in the supply chain industry, but a norm.

How to Use Augmented Reality to Pitch Your Next Consumer Product

COVID-19 caused a rapid shift toward remote work and, thus, fueled the rise in adoption of Microsoft Office 365 services, including Exchange Online. While a growing number of users are choosing Exchange Online, the native data protection tools may be insufficient to ensure data protection and compliance retention. And this is where Exchange Online backups come into play. This article covers the five main reasons why businesses need to back up Office 365 Exchange Online. Additionally, it includes practical tips on how to minimize data loss based on the industry’s backup best practices. Reason #1. Microsoft isn’t responsible for protecting your Exchange Online data Microsoft is legally responsible for its host infrastructure and platform availability. But the company is not responsible for data protection or data loss outside occasional outages or disruptions on Microsoft’s side. The Microsoft platform does become unavailable. In 2020 alone, Microsoft had three outages that brought Office 365 tools, including Teams, Exchange and Outlook, down for a total of 11 hours during ten days. Microsoft is clear that they Exchange Online though. If email data is lost or corrupted due to accidental or malicious actions, the recovery of emails and other data in mailboxes is the customer’s responsibility. Even in the service agreement, Microsoft recommends that you regularly back up the data stored in Microsoft 365 applications to minimize possible data loss. don’t back up You can protect Exchange Online emails with native access control features and multi-factor authentication. But according to the Microsoft , data protection and account access management fall under your responsibility. This means that if your data is accessed by cybercriminals, Microsoft won’t be the one to blame. Shared Responsibility Model Misconceptions about the liabilities of software as a service (SaaS) providers are commonplace. Research shows that 37% of organizations solely rely on SaaS vendors like Microsoft to protect their application data. Another 33% don’t think that SaaS application data needs to be backed up at all. These misconceptions put your Exchange Online data at greater risk of being attacked or stolen, which brings us to the next point. Reason #2. Your data is vulnerable to external threats Your critical company data and user contact details make Exchange Online a treasure trove for cybercriminals. Here are the three main types of external threats you should be aware of: . Users can receive infected emails with links to malicious websites or malware. Once they open a link, criminals steal credentials and get access to critical data. Phishing . Users can download this type of malware by opening a phishing email or an infected file. Once malware invades your system, it locks your IT environment until your organization pays the ransom. Ransomware . Viruses and spyware can collect your credentials and other sensitive data. Spyware and viruses Microsoft is a reliable service provider. However, user behavior can open Exchange Online data to cyberattacks and ransomware. In 2019 and 2020, Microsoft faced a massive phishing attack that compromised customers’ business email accounts in 62 countries. In 2021, an attack on Microsoft Exchange Server caused a massive data breach that affected at least 30,000 users. As Microsoft isn’t responsible for your data protection, adding an extra layer of security makes a lot of sense. Exchange Online backups won’t save you from attacks, but they guarantee the recoverability of mailboxes with no or minimal data loss. Additionally, backups enable point-in-time recovery, which is outside the scope of the Exchange Online functionality. You can restore data from the backups made before the attack and, thus, avoid paying ransoms. Criminals can do a lot of harm, but sometimes threats come from people within the company too. Reason #3. Your employees can delete or compromise data Your employees can delete emails and accounts in Exchange Online or even cause a data leak by sending an email with confidential information to someone outside the company. The employee’s actions can be accidental or intentional. The latter is particularly dangerous because your staff knows the company’s weaknesses and can cause irreversible damage. An Exchange Online mailbox allows users to restore deleted objects for only 14-30 days, depending on the account settings. After 30 days, deleted objects aren’t recoverable. So Exchange Online backups are the only chance to retrieve this data. Leading backup providers allow you to restore emails (with all attachments), contacts or calendar items in minutes without recovering the entire mailbox. What’s more, you can choose whether to recover items to the original location or another mailbox (for example, when you need to restore the folders of a deleted account). With access control, the principle of least privilege, multi-factor authentication and similar data security tools, you can minimize human errors and even prevent damage. But is it safe to rely on Microsoft native protection? Reason #4. Microsoft protection isn’t enough Microsoft offers a variety of native tools to protect Exchange Online mailboxes, including privileged access management, data encryption with sensitivity labels, email-filtering service against phishing and malware (Exchange Online Protection and more advanced Microsoft Defender). However, you need more comprehensive and reliable protection. Protection capabilities vary across Office 365 plans. Most features, including message encryption and Data Loss Prevention (DLP), are available in the Office 365 E3 and E5 plans. Threat protection (Microsoft Defender) and Office 365 Cloud App Security are added only to the most expensive plan, the E5 plan. All Office 365 users can take advantage of identity and access management. However, according to research by Vectra, a network threat detection provider, malicious applications are bypassing Microsoft embedded security controls and multi-factor authentication in 96% of the Office 365 customers they have studied. Microsoft native data protection does offer some tools to help you prevent attacks and unauthorized access. But you need more. This brings us to the second reason why you need to back up Exchange Online—the risk of external threats. In case an external threat appears, backups will allow you to resume your IT operations and minimize data loss. Reason #5. You can have legal and regulatory penalties Businesses can be subject to a variety of legal standards and regulations, such as European General Data Protection Regulation (GDPR) or the US Payment Card Industry Data Security Standard (PCI DSS). The law requires companies to retain Exchange Online emails and accounts for legal compliance. So in case of an audit or a trial court, the company should retrieve this data for e-discovery and further investigation. For compliance purposes, Exchange Online allows users to configure retention policies and use In-Place or Litigation Hold where mailbox objects are retained immutably. But these tools are not as effective as you may think: Retention planning can be confusing, especially with several Office 365 workloads. Your employee can forget to include Exchange Online accounts in the policy or lose data due to employee turnover or data migration. If you delete a user account, its mailbox will be marked for deletion too, even if it’s currently on hold. Once you lose an account or mailbox, you lose the chance to restore this data without a backup. If you’re lucky enough you can notice the loss and recover objects within 14-30 days. But it’s a bad strategy to rely on luck, as this can cost you eye-watering compliance fines. An effective backup strategy, on the other hand, can allow you to configure automatic backup workflows and flexible retention policies to ensure that no data is lost. Let’s explore this in more detail. Stay in control of your data with Exchange Online backups With regular and reliable Exchange Online backups, you can easily recover emails and accounts, restore ransom-free mailboxes and comply with regulatory requirements. Here are a few tips on how to make your Exchange Online backup strategy more effective and resilient to threats: . Exchange Online mailboxes can consume a lot of storage space, so ensure that your backups are lightweight and don’t put an extra load on the network. Use incremental backups Keep your backups protected from ransomware and malware by storing them offline, on a local computer or a server. Store on-premise. . Set role-based access control and multi-factor authentication to ensure the security of your backup activities. Control access to backups Ensure that your backups are regular and complete to avoid any data loss. Automate your backup activities. . Optimize your storage space usage with rotation schemes, such as Grandfather, Father, Son (GFS) that allows you to rotate your backups on a daily, monthly or yearly basis. Adopt flexible rotation schemes Backups mitigate the risk of data loss, ensure business continuity and keep you away from compliance fees. With a reliable partner in your corner, you can be sure that your data is always recoverable. Wrapping up Millions of people use Exchange Online to send emails, manage their calendars and contacts. With so much data circulating in mailboxes, Exchange Online is a treasure trove for ransomware and other criminals. But while many users rely on Microsoft native data protection, these tools can fail to prevent attacks. Despite the common belief, Microsoft isn’t legally responsible for data protection, recovery, and access control. Users may face data loss during occasional outages or due to human mistakes and poor data management. And if this happens, Exchange Online backups become the only chance to restore data and avoid ransoms or compliance fees. Also published . here

The Top 5 Reasons to Back up Exchange Online

Businesses around the world are embracing the potential application of Augmented Reality and Virtual Reality in building their products. This emerging technology is being used across leading industries such as those seen in the lead image above. Therefore, it is crucial for businesses to understand the importance of building customized solutions that cater to the needs of their audience as well as leave a powerful everlasting impact on their users. This can be achieved through “ ”, a technique that is commonly used while designing applications, websites, and other products to increase business visibility and potential reach. branding In this article, I will be showing you how you to apply branding to AR/VR experiences based on my 2+ years of research and careful observation of AR experiences across various industries. Brand Style Guide Branding begins with creating a brand style guide document. A brand style guide is a set of design standards that a company sets, follows and enforces for it’s fleet of products to ensure that they look and feel consistent. Brand Style Guides are also termed as brand guideline document, style guide or brand manual. Brand Style Guide = Colors + Typography + Logo + 3D Models Creating a guide only for 2D experiences( ) does not act as a substitute for 3D experiences. Transitioning from a 2D experience to a 3D experience should be smooth. Incorporate an on-boarding screen before your user begins exploring the 3D experience. View in AR buttons and a screen to show a 3D model in a 3D view are common ways of achieving a smoother transition from a 2D experience to a 3D experience. mobile applications and websites The other articles in the above series are also worth reading! Logos At the time of writing this article, there is no standard set of guidelines for creating 3D logos( ). obj, fbx These standards have been maintained for the past several years, especially when Android and iOS users boomed. Companies like Google and Apple that developed their own marketplaces for Android( ) and iOS(App Store), advice designers to follow these set of guidelines while creating logos for their apps. Ultimately, the apps then get reviewed and released into the app marketplaces, from where users download the apps to their smartphones. Google Play Store There is a high chance that, in the future, there will be a marketplace that lets users download apps to their smart Augmented Reality glasses. That is when the design standards for AR experiences will get more streamlined, especially for logos, or more specifically, 3D logos. Designers have been using tools like Adobe Photoshop and Adobe Illustrator in the past decade to design logos. Vectary is a new design tool that makes it easy for designers to create 3D logos It is highly recommended that designers learn this tool and come up with different logo formats that will work well for apps that can run on smart AR glasses. 3D Models Character models that appear friendly perform well, especially, if the models add some humor to the overall AR experience. If you already have a mascot or a strong persona for your brand, you should create a 3D model of it and use it in all your marketing campaigns. In 2019, Sony Pictures had developed a mobile app where users could place animated 3D models like Spiderman and Mysterio from the Spiderman: Far from Home movie. It served as an excellent pre-release marketing strategy for the movie. The movie earned 1 billion dollars globally in just 24 days after it was released. Use Custom Materials and Shaders This section of the article is inclined more towards your company’s technical department i.e designers and developers. When detecting plane surfaces, graphic components like materials and shaders should be matched according to the branding style guide of your company. Visualization of planes is commonly done using a default material or simply showing a white 3D grid. Although this common visualization process serves the purpose, it’s not a strong visual representation of your brand. Ask your Technical Artists to create custom materials and shaders rather than using the ones available in ARCore/ARKit( ) by default. or whatever SDK they are using Notice the use of red, blue, yellow and green colors in the . These colors are the same as Google’s brand colors. This app serves as a perfect example of branding in AR/VR experiences using customized materials and shaders in their 3D models. Google ARCore Elements app ADDITIONAL RESOURCES👇 Get my ebook Introduction to UX Design for AR Experiences Also published at: https://medium.com/xrdi/how-to-apply-branding-to-ar-vr-experiences-4a07d5c347f0

A Beginner's Guide to Applying Branding to AR/VR Experiences

AI and Machine Learning are hence, leading to RISE OF AI IS ON THE RISE, shaping the future in Cybersecurity, AI-based cybersecurity tools as a phoenix. With a recent study finding that nearly two-thirds of organizations are using or plan to use AI capabilities in their security operations by 2023. The days of deliberate, human-driven malware attacks are fading fast. We’re now seeing a surge in AI-powered attacks that can bypass even the most sophisticated security defenses. No wonder, then, that the demand for artificial intelligence cybersecurity tools is also growing at an exponential rate. Cybersecurity experts are turning to to be able to keep up with the variety and speed of modern day cyber threats. artificial intelligence AI-based tools can detect patterns in data, quickly identify anomalies and learn from their mistakes — all tasks that would prove too hard or slow for humans. Artificial intelligence is like climbing a tree to try and reach the moon; one can report steady progress, all the way to the top of the tree. What is Artificial Intelligence in Cyber Security? Artificial intelligence is a fancy way to describe the process of building machines that can learn and respond to their environment. In , artificial intelligence tools are programmed to look for certain, known indicators of risk or threat. cybersecurity Once those indicators are identified, the system can take automatic action to stop the threat before damage is done. How Does Artificial Intelligence in Cyber Security Work? One common example of AI’s use in cybersecurity comes from email filtering programs like Gmail. When an email hits your inbox with a suspicious link or attachment, Gmail sends a warning and deletes the email before you’re able to click on it. This works because Gmail has been trained using millions of examples of suspicious emails from users around the world. It has learned that certain links or attachments often indicate malicious intent, so when it sees those links or attachments in an incoming email, it flags them as potentially dangerous and takes action to protect you from them. AI Cyber Security Tools - What Are These? As technology dramatically improves, AI has become a huge buzz word. With the advancement of technology and , artificial intelligence security tools are also becoming smarter and more efficient in every way. evolution of AI These types of cyber security tools are highly sophisticated and can automate the process of threat detection and eradication by employing , deep learning algorithms and automation. machine learning The artificial intelligence cybersecurity are the leading next-generation cybersecurity solutions that get things done. -enabled security and products can detect and respond to incidents with minimal or zero input from humans. tools AI tools cybersecurity They protect the entire data layer and provide deep visibility across the enterprise. The solution detects, tracks, and responds to threats in real-time. The cyber security system with AI can monitor large amounts of data and spot anomalies, identify hackers' methodologies, and recognize attacks. That's because when it comes to preventing security breaches, AI-based tools have a lot of advantages—including the ability to detect and stop threats before they happen, and perform tasks more effectively than humans. It also has many features like: -Unlimited scalability -Automatic updates -Flexible deployment options -Advanced threat protection -Advanced threat prevention Today’s cyber criminals are using machine learning to better understand the behavior of their targets and launch more precise attacks, so it makes sense that organizations would also want to harness these same technologies to stay ahead of them. Top 8 AI-Based Cyber Security tools You Must Try In 2022 Whether you already know these tools or not, one thing is for certain: these tools are some of the best available today. I've talked to a bunch of people who think AI has a lot of potential in the future and they argue that it's only a matter of time before AI starts becoming an integral part of our daily lives. And they're right! In fact, it's already happening. So what are some recommendations for the Top 7 Cyber Security Tools That Use AI - Must Try In 2022? Check out my list below! Darktrace Antigena Antigena is Darktrace’s active self-defence product, extending its core capabilities to detect and replicate digital antibody functions that identify and neutralize threats. Darktrace Antigena identifies and protects against unknown threats without prior knowledge of attacks, rules, or signatures. Darktrace then can respond automatically to threats, which enables rapid response without disruption of normal business activity. - Try It Here WP Hacked Help (WPHH) Reduce your website breach risk, don’t add to it. WP Hacked Help is a WordPress security service provider that has taken the world of cyber security by storm in 2022. Their tool, First Ever, AI based WordPress malware scanner, is Engineered from the ground up to be secure (WordPress) websites (you must know that wordpress is the most popular CMS and hence is the top target for hacking). It including features like AI based wordpress website malware scanner. What makes it unique and revolutionary? It uses AI and machine learning (ML) to quickly analyze millions of hacked websites and identify many different types of threats – from malware exploiting zero-day vulnerabilities to identifying risky behavior that might lead to getting your wordpress hacked. Their AI based wordpress scanner tool learns over time, drawing from the past to identify new types of attacks. Histories of hacker build profile , assets, and networks, allows AI to detect and respond to deviations from established norms. Try It Here bioHAIFCS BioHAIFCS (Bio-inspired Hybrid Artificial Intelligence Framework for Cybersecurity) is a bio-inspired, hybrid artificial intelligence framework for cybersecurity that combines timely and bio-inspired machine learning methods. It was first developed to protect military information systems, applications, and networks. The program incorporates the Hybrid Evolving Spiking Anomaly Detection Model (HESADM), which is used to prevent cyber-attacks, because these types of attacks cannot be overcome by passive security measures; the Evolving Computational Intelligence System for Malware Detection (ECISMD); and the Evolutionary Prevention System from SQL Injection (ePSSQLI) attacks. : GitHub https github.com sumendrabsingh/CyberSecTK-Library Cyber Security Tool Kit (CyberSecTK) CyberSecTK is a Python library for preprocessing and feature extraction of cyber-security-related data with the purpose of bridging the gap between cybersecurity and machine learning techniques. The CyberSecTK (Cybersecurity Toolkit) is a suite of cybersecurity tools and modules. It helps cyber experts to implement a basic machine-learning pipeline from scratch. Try It Here Cognito by Vectra Vectra's Cognito platform is designed to detect and respond to cyberattacks within the cloud, data center, IoT, and enterprise networks. With Cognito, organizations can automate threat detection, empower their security teams with actionable insights across an entire deployment, and gain visibility into complex environments. Try It Here - https://www.vectra.ai DefPloreX DefPloreX is a machine learning toolkit designed to detect large-scale e-crime on the internet. It is a flexible toolkit that is based on open-source libraries, enabling it to efficiently analyze millions of defaced web pages. The DefPloreX system uses machine learning and data visualisation techniques to turn unstructured data into meaningful descriptions. When used with collected data on a large volume of web incidents, DefPloreX automatically groups similar defaced pages into clusters and organises web incidents into campaigns. Repository: https://github.com/trendmicro/defplorex Github IBM QRadar Advisor IBM QRadar Advisor with Watson is a cognitive artificial intelligence platform that supports security professionals through the incident and risk analysis, triage, and response process. Check out - https://www.ibm.com/in-en/products/cognitive-security-analytics/details Sophos’ Intercept X tool Intercept X is a cybersecurity tool that leverages the deep learning capabilities of Sophos to protect networks against threats. It shifts endpoint security from a reactive to a predictive approach, both preventing known and never-seen-before threats. Sophos Intercept X employs a defense-in-depth approach to endpoint protection. One of its primary security techniques is enforcing data execution prevention, which can prevent code injection attacks. It also has other features like stack pivot and heap spray allocation. https://www.sophos.com/en-us/products/endpoint-antivirus Check out: Targeted attack analytics (TAA) by Symantec Symantec's targeted attack analytics (TAA) tool provides a variety of benefits: cloud-based analytics that continuously adapt to new attack techniques, continuous delivery of attack detections, and the ongoing addition of new attack analytics. Advanced Threat Protection provides multiple incidences of attack detections combined with AI-driven and human analysis customized to each customer's environment. Is AI or machine learning enough to stop cybercrime? Machine learning does some things really well, such as quickly scanning large amounts of data and analyzing it using statistics. Cybersecurity systems generate reams of data, so it's no wonder the technology is such a useful tool . “Data tells a story,” “ If you understand how to analyze the data, you should be able to come up with the deviations from the norm and how to protect your online business.” says Umar Shreef, a tech savvy small business owner in Toronto. Hope you find this article interesting. That’s a wrap! I’ll be bringing out , which will be arriving shortly! Part 2 About Me - I’m Daniel Kebbe, , Operations & Incident Response at . I help seamlessly monitor and analyse cyber security trends and threats using artificial intelligence. Before that , I worked at various software companies such as virtual-reality (VR) company Magic Leap, travel metasearch engine Hipmunk and BlackBerry Ltd. Director Cyber Security Redblink I also have a passion to share (good stuff) at my newsletter. substack

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