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Our definition of 'goal setting' isn't what it used to be. Somewhere along the line, we got it twisted – and now, kids who have barely got their driver's license are expected to plan their entire future. We carry this pressure into adulthood, too. I know plenty of people who have nailed down exactly where they're (allegedly) going to be in five years' time. Despite the supposed benefits of future planning, they're very stressed individuals. Here's what I think happens. Job titles, cities, and companies are all tangible things we can grasp with our minds. It's easy to say, "I plan to be a Senior Vice President of something or other at this company in five years" – so we hold on tight to those specifics. The problem is that, in prescribing a future for yourself, you leave little room for unexpected opportunities or a change of heart. You box yourself in when there was never a need to use boxes in the first place. Let me dig into this a little deeper – you'll see what I mean. Why We Prescribe I am forever haunted by the statistic that end up dropping out. The actual dropping out part doesn't scare me; it's the implication. 40 percent of US college students We feel so pressured to line up our ducks, to prescribe our futures, that the detours and roadblocks we encounter later on are seen as failures. Even as adults, why are we so hellbent on having a rigid five-year or ten-year plan? How on earth can we predict what we'll want, who we'll be, and where we'll be in a decade? If I made decisions now based on what I wanted ten years ago... well, things would be different. Let's put it that way. So, why do we do this? We're Conditioned This Way It's easy to see how rigid planning stems from childhood; we're raised with the ideas of career progression, degrees, and qualifications, and having defined career paths that lead logically from one place to the next. There's little talk of flexibility. At my school, you were either going to college, or you were lost. It stands to reason that we'd come away from this conditioning with a set-in-stone mindset: you choose your career now, and you plan it out to the nth degree. We Want A Sense of Security of Dr. Thema Bryant-Davis, a psych professor at Pepperdine University, "It’s a way of dealing with worry and can give people a false sense of control." In the words I can understand that. I've been there myself. When all else feels chaotic, there's a temptation to retreat into our comfort zone and make rigid plans for the future. We don't want any surprises – we just want what we expect. Of course, we know deep down that life has other ideas. Planning our lives seems like the best way to combat unexpected changes... but in reality, it's like locking our knees before hitting the ground. We make ourselves so inflexible that even a short fall leaves us with a broken bone. Family and Societal Expectations It's easy to start prescribing your life as a way to explain or justify yourself to others. If you're not in a stable job at the moment, for instance, maybe you'll create a plan for the future to soothe family members, friends, and peers. But again, this comes with an expiration date. We may be able to fool others for a little while – but we can't keep up that façade forever. It's human nature to change our minds and switch paths; trying to stick it out despite feeling like you're going in the wrong direction is counterintuitive at best, and damaging at worst. But Isn't Planning Helpful, Usually? Great point – yes, it is. Planning is both helpful and essential to getting the life you want. But there is a difference between planning and prescribing yourself to a certain path. Planning involves setting goals, making budgets, and taking stock of what you already have. It's like mapping out the route to your destination, but knowing that you can change course if needed. I'd also say that mindful planning comes from your values and passions. Instead of looking at a career progression chart for your area of study, you should plan your future around the things you know bring you the most joy. Why? Because typically, your values and passions are the things that don't change. The Psychology of Open-Ended Planning I frequently think about this quote by one of the best philosophers of all time, Ludwig Wittgenstein: “A man will be imprisoned in a room with a door that’s unlocked and opens inwards; as long as it does not occur to him to pull rather than push." It's hard to know exactly what he's referring to here. The way I interpret it, though, is that doors to new opportunities will remain closed if you don't realize they're able to be opened. This is what I believe happens to us when we plan our lives out too rigidly. We end up clueless as to the possibilities lying just outside our peripheral – because why would we bother looking when everything is already decided? Open-ended planning sidesteps this problem by actively putting questions in the air. What could you be doing in five years' time? What could your career path look like? What new opportunities can you take advantage of in the meantime to explore your passions? You acknowledge the infinite options available to you, and therefore, it does occur to you to "pull rather than push." Values-Based Planning 101 Rounding up everything I've said so far, here's my hypothesis: we need to be engaging in values-based planning rather than prescriptive planning. There's a clear distinction between the two. With prescriptive planning, you are largely focused on the way your future looks and sounds. What's your job title? What do you earn? In values-based planning, you're focusing on how your future feels. Knowing what you respond to emotionally, and knowing where your passions and values lie, you're able to construct a picture of the future that will gel with your personality regardless of where you end up. A rigid, prescriptive, plan might be, "I want to finish this degree, get a job in X field and work my way up the ladder within Y company." A flexible, open-ended five-year plan might be, "I want to end up in a position where I'm working with people on an individual level and helping them to solve problems." That could mean a lot of different things – so you can take the time to explore and find out what that looks like in practice. You can see how one plan is much more open to unexpected opportunities and changes, while the other has a much narrower path. Yes, the more ambiguous option feels a little intimidating – but that's the beauty of it. A little uncertainty is a small price to pay for flexibility and uncapped potential. When Prescriptive Planning Helps By all means, there are certain situations where making a rigid timeline can be your saving grace. For instance, you might be working toward a 10-mile run in six months' time. You might have a specific career path in mind that requires certain qualifications, or you may be working toward a promotion at your current job – in which case you'll need to plan out the steps to get there and make sure they're achievable within a certain timeframe. In these cases, planning a rigid timeline is your roadmap – it keeps you on the path and provides a sense of security in the face of uncertainty. As soon as you start talking about five or ten years down the track, though, you're essentially making plans for someone you don't even know. That person could have completely different wants and needs than you do now. By all means, keep your goals in sight – but make sure you're open to the unexpected and embrace opportunities as they come. That's how real growth happens. Wrap Up It's easy to get caught up in what feels like a logical plan; life rarely works out the way we expect it to. (In fact, it usually deviates in very drastic ways). That doesn't mean you should abandon all hope for progress – just that you should always be ready to adapt when necessary. Center yourself around the things that ignite your passions, and don't put a low ceiling over your head as a self-inflicted cap on your potential. I'd love to hear from you if anything here resonated, so feel free to respond by email or add a comment below. Until next time! If you enjoyed this article, I’d love to hear from you. Reply to this or at me and I'll do my best to get back to everyone! email tweet @ScottDClary

It's Important to Plan for the Future, But Don’t Prescribe It

Since the wave of digitization is sweeping businesses, managing an enterprise has become a much easier task. Enterprises now utilize applications or software like Customer Relationship Management or CRM, project management applications, ERP, and more to carry out several business-critical tasks. However, the widespread use of these applications may also come at a cost as data breaches have been becoming more common since 2020. For this reason, Identity and access management or IAM architects have shed light on the importance of enterprise application security. Vulnerabilities in an Enterprise Application Enterprises are always on the lookout for opportunities to drive digital transformation. They do so by introducing certain technological innovations. For example, the creation of enterprise IoT and Cloud computing, and more. Although these innovations have significantly contributed to the digitization of an enterprise and its subsequent growth, they can also be an entry point for hackers and malware. These entry points are known as vulnerabilities in an application. Let’s take a look at a few of the most common ones found in applications. Lack of Access Control A surprising number of data breaches take place internally. That is, the employees working within the company may consciously or unconsciously break access protocol. It can also occur when user restrictions are not implemented properly. Therefore, a lack of control over who accesses what in the application is considered to be a vulnerability. Exposure of Sensitive Data This can be a big problem for the enterprises that collect extensive information about their employees and their customers. This involves information like addresses, , account details, etc. The databases that house this information are among the most common targets for cyberattacks and may result in the unauthorized distribution of sensitive data. passwords Non-functioning Authentication Authentication is a measure that is present in every enterprise application. This security measure is essential as it plays a vital role in the aforementioned user restriction. Applications usually utilize the security along with the session management application functions to ensure security. security two-factor authentication Security Misconfigurations Finally, applications could also suffer from security misconfigurations. These can be due to various reasons like default configurations that are not secure, misconfigured HTTP headers, or incomplete configurations. Tools that Promote Enterprise Application Security At present, the tools that an enterprise uses to ensure the security of their applications can be categorized into two types. Firstly, there are the tools that test the existing security measures put in place in the application. The other type of tool is the one that fortifies or adds to the security measures. 1. Types of testing tools The testing is carried out using the following tools: Static application testing: This tool essentially reads the code that the application is created from to ensure no mistakes that could lead to security gaps. Dynamic application testing: These tools detect gaps in the code while it is running. To a developer, this kind of testing mimics a cyberattack so that the developers can work towards reinforcing the code. Hence, the name dynamic. 2.  Variations of Fortifying Tools Under the fortifying tools, one will find the following: RASP: The Runtime Application Self-protection tool acts as a tester and a fortifier simultaneously. It does so by monitoring the environments present on the desktop and even mobile devices. Anti-Tampering software: This software functions to prevent cybercriminals from obtaining access to the code of an application. Threat detector: This tool is usually used by professionals to ensure that the environment in which the application is running is safe. Therefore, aspects like the state of the environment, potential threats, and compromised devices can be found. Benefits of Implementing Enterprise Application Security From the aforementioned points, it becomes clear that an enterprise application with the required security measures offers an unprecedented sense of safety to the users of the applications. In addition to this, other benefits make application security desirable to IAM architects and enterprises alike. These benefits include: Real-time detection: Cyberattacks are usually detected quite quickly, given the number of security measures that are put into place. Some measures also detect high-risk activity through behavior analysis. The detection can also be automated in some cases. Versatile integration: The security measures are compatible with multiple applications, irrespective of whether it is a cloud platform or a SaaS platform. Compliance monitoring: The testing tools mentioned before will be used to ensure that the application complies with the safe practices and regulations of data security. These tools can also monitor the critical infrastructure and prevent possible data loss. Enterprise application security (EAS) is transforming the information technology landscape. As the pace of digital business accelerates and the complexity of enterprise IT grows, regulatory requirements are demanding more serious attention. No longer a “nice-to-have”, many boardrooms now acknowledge that is essential to securing infrastructure, data, and applications in today’s digital economy. enterprise application security

Why IAM Architects Prescribe Enterprise Application Security

Conversations With AI: Empathy, Peace, And Humor

Gesprekke met AI: empatie, vrede en humor

İT-lə danışıqlar: empatiya, barış və humor

AI সঙ্গে কথোপকথন: অনুপ্রেরণা, শান্তি এবং Humor

Samtaler med AI: Empati, fred og humor

Conversaciones con AI: empatía, paz y humor

AI- ի հետ խոսակցություններ: Empathy, Peace, and Humor

AIとの会話:共感、平和、ユーモア

Conversas com a IA: empatia, paz e humor

Разговоры с ИИ: эмпатия, мир и юмор

Bisedimet me AI: Empati, Paqja dhe Humori

Mazungumzo na AI: Empathy, Amani, na Humor

Bilmiz: Empathy, Peace, and Humor

As the capabilities of LLMs (Large Language Models) and adjacent tools like embedding models grew significantly over the past year, more and more developers are considering integrating LLMs into their applications. Since LLMs often require dedicated hardware and significant compute resources, they are most commonly packaged as network services that provide APIs for access. This is how the APIs for leading LLMs like OpenAI or Google Gemini work; even run-your-own-LLM tools like Ollama wrap the LLM in a REST API for local consumption. Moreover, developers who take advantage of LLMs in their applications often require supplementary tools like Vector Databases, which are most commonly deployed as network services as well. In other words, LLM-powered applications are a lot like other modern cloud-native applications: they require excellent support for REST and RPC protocols, concurrency and performance. These just so happen to be the areas where Go excels, making it a fantastic language for writing LLM-powered applications. This blog post works through an example of using Go for a simple LLM-powered application. It starts by describing the problem the demo application is solving, and proceeds by presenting several variants of the application that all accomplish the same task, but use different packages to implement it. All the code for the demos of this post is available online. A RAG server for Q&A A common LLM-powered application technique is RAG - Retrieval Augmented Generation. RAG is one of the most scalable ways of customizing an LLM’s knowledge base for domain-specific interactions. We’re going to build a RAG server in Go. This is an HTTP server that provides two operations to users: Add a document to the knowledge base
Ask an LLM a question about this knowledge base In a typical real-world scenario, users would add a corpus of documents to the server, and proceed to ask it questions. For example, a company can fill up the RAG server’s knowledge base with internal documentation and use it to provide LLM-powered Q&A capabilities to internal users. Here’s a diagram showing the interactions of our server with the external world: In addition to the user sending HTTP requests (the two operations described above), the server interacts with: An embedding model to calculate vector embeddings for the submitted documents and for user questions.
A Vector Database for storing and retrieving embeddings efficiently.
An LLM for asking questions based on context collected from the knowledge base. Concretely, the server exposes two HTTP endpoints to users: /add/: POST {"documents": [{"text": "..."}, {"text": "..."}, ...]}: submits a sequence of text documents to the server, to be added to its knowledge base. For this request, the server: Calculates a vector embedding for each document using the embedding model.
Stores the documents along with their vector embeddings in the vector DB. /query/: POST {"content": "..."}: submits a question to the server. For this request, the server: Calculates the question’s vector embedding using the embedding model.
Uses the vector DB’s similarity search to find the most relevant documents to the question in the knowledge database.
Uses simple prompt engineering to reformulate the question with the most relevant documents found in step (2) as context, and sends it to the LLM, returning its answer to the user. The services used by our demo are: Google Gemini API for the LLM and embedding model.
Weaviate for a locally-hosted vector DB; Weaviate is an open-source vector database implemented in Go. It should be very simple to replace these by other, equivalent services. In fact, this is what the second and third variants of the server are all about! We’ll start with the first variant which uses these tools directly. Using the Gemini API and Weaviate directly Both the Gemini API and Weaviate have convenient Go SDKs (client libraries), and our first server variant uses these directly. The full code of this variant is in this directory. We won’t reproduce the entire code in this blog post, but here are some notes to keep in mind while reading it: Structure: the code structure will be familiar to anyone who’s written an HTTP server in Go. Client libraries for Gemini and for Weaviate are initialized and the clients are stored in a state value that’s passed to HTTP handlers. Route registration: the HTTP routes for our server are trivial to set up using the routing enhancements introduced in Go 1.22: mux := http.NewServeMux()
mux.HandleFunc("POST /add/", server.addDocumentsHandler)
mux.HandleFunc("POST /query/", server.queryHandler) Concurrency: the HTTP handlers of our server reach out to other services over the network and wait for a response. This isn’t a problem for Go, since each HTTP handler runs concurrently in its own goroutine. This RAG server can handle a large number of concurrent requests, and the code of each handler is linear and synchronous. Batch APIs: since an /add/ request may provide a large number of documents to add to the knowledge base, the server leverages batch APIs for both embeddings (embModel.BatchEmbedContents) and the Weaviate DB (rs.wvClient.Batch) for efficiency. Using LangChain for Go Our second RAG server variant uses LangChainGo to accomplish the same task. LangChain is a popular Python framework for building LLM-powered applications. LangChainGo is its Go equivalent. The framework has some tools to build applications out of modular components, and supports many LLM providers and vector databases in a common API. This allows developers to write code that may work with any provider and change providers very easily. The full code for this variant is in this directory. You’ll notice two things when reading the code: First, it’s somewhat shorter than the previous variant. LangChainGo takes care of wrapping the full APIs of vector databases in common interfaces, and less code is needed to initialize and deal with Weaviate. Second, the LangChainGo API makes it fairly easy to switch providers. Let’s say we want to replace Weaviate by another vector DB; in our previous variant, we’d have to rewrite all the code interfacing the vector DB to use a new API. With a framework like LangChainGo, we no longer need to do so. As long as LangChainGo supports the new vector DB we’re interested in, we should be able to replace just a few lines of code in our server, since all the DBs implement a common interface: type VectorStore interface {
    AddDocuments(ctx context.Context, docs []schema.Document, options ...Option) ([]string, error)
    SimilaritySearch(ctx context.Context, query string, numDocuments int, options ...Option) ([]schema.Document, error)
} Using Genkit for Go Earlier this year, Google introduced Genkit for Go - a new open-source framework for building LLM-powered applications. Genkit shares some characteristics with LangChain, but diverges in other aspects. Like LangChain, it provides common interfaces that may be implemented by different providers (as plugins), and thus makes switching from one to the other simpler. However, it doesn’t try to prescribe how different LLM components interact; instead, it focuses on production features like prompt management and engineering, and deployment with integrated developer tooling. Our third RAG server variant uses Genkit for Go to accomplish the same task. Its full code is in this directory. This variant is fairly similar to the LangChainGo one - common interfaces for LLMs, embedders and vector DBs are used instead of direct provider APIs, making it easier to switch from one to another. In addition, deploying an LLM-powered application to production is much easier with Genkit; we don’t implement this in our variant, but feel free to read the documentation if you’re interested. Summary - Go for LLM-powered applications The samples in this post provide just a taste of what’s possible for building LLM-powered applications in Go. It demonstrates how simple it is to build a powerful RAG server with relatively little code; most important, the samples pack a significant degree of production readiness because of some fundamental Go features. Working with LLM services often means sending REST or RPC requests to a network service, waiting for the response, sending new requests to other services based on that and so on. Go excels at all of these, providing great tools for managing concurrency and the complexity of juggling network services. In addition, Go’s great performance and reliability as a Cloud-native language makes it a natural choice for implementing the more fundamental building blocks of the LLM ecosystem. For some examples, see projects like Ollama, LocalAI, Weaviate or Milvus. Credits: Eli Bendersky Photo by Verne Ho on Unsplash This article is available on The Go Blog under a CC BY 4.0 DEED license. As the capabilities of LLMs (Large Language Models) and adjacent tools like embedding models grew significantly over the past year, more and more developers are considering integrating LLMs into their applications. Since LLMs often require dedicated hardware and significant compute resources, they are most commonly packaged as network services that provide APIs for access. This is how the APIs for leading LLMs like OpenAI or Google Gemini work; even run-your-own-LLM tools like Ollama wrap the LLM in a REST API for local consumption. Moreover, developers who take advantage of LLMs in their applications often require supplementary tools like Vector Databases, which are most commonly deployed as network services as well. Ollama In other words, LLM-powered applications are a lot like other modern cloud-native applications: they require excellent support for REST and RPC protocols, concurrency and performance. These just so happen to be the areas where Go excels, making it a fantastic language for writing LLM-powered applications. This blog post works through an example of using Go for a simple LLM-powered application. It starts by describing the problem the demo application is solving, and proceeds by presenting several variants of the application that all accomplish the same task, but use different packages to implement it. All the code for the demos of this post is available online . is available online A RAG server for Q&A A common LLM-powered application technique is RAG - Retrieval Augmented Generation . RAG is one of the most scalable ways of customizing an LLM’s knowledge base for domain-specific interactions. Retrieval Augmented Generation We’re going to build a RAG server in Go. This is an HTTP server that provides two operations to users: RAG server Add a document to the knowledge base Ask an LLM a question about this knowledge base Add a document to the knowledge base Ask an LLM a question about this knowledge base In a typical real-world scenario, users would add a corpus of documents to the server, and proceed to ask it questions. For example, a company can fill up the RAG server’s knowledge base with internal documentation and use it to provide LLM-powered Q&A capabilities to internal users. Here’s a diagram showing the interactions of our server with the external world: In addition to the user sending HTTP requests (the two operations described above), the server interacts with: An embedding model to calculate vector embeddings for the submitted documents and for user questions. A Vector Database for storing and retrieving embeddings efficiently. An LLM for asking questions based on context collected from the knowledge base. An embedding model to calculate vector embeddings for the submitted documents and for user questions. vector embeddings A Vector Database for storing and retrieving embeddings efficiently. An LLM for asking questions based on context collected from the knowledge base. Concretely, the server exposes two HTTP endpoints to users: /add/: POST {"documents": [{"text": "..."}, {"text": "..."}, ...]} : submits a sequence of text documents to the server, to be added to its knowledge base. For this request, the server: /add/: POST {"documents": [{"text": "..."}, {"text": "..."}, ...]} Calculates a vector embedding for each document using the embedding model. Stores the documents along with their vector embeddings in the vector DB. Calculates a vector embedding for each document using the embedding model. Stores the documents along with their vector embeddings in the vector DB. /query/: POST {"content": "..."} : submits a question to the server. For this request, the server: /query/: POST {"content": "..."} Calculates the question’s vector embedding using the embedding model. Uses the vector DB’s similarity search to find the most relevant documents to the question in the knowledge database. Uses simple prompt engineering to reformulate the question with the most relevant documents found in step (2) as context, and sends it to the LLM, returning its answer to the user. Calculates the question’s vector embedding using the embedding model. Uses the vector DB’s similarity search to find the most relevant documents to the question in the knowledge database. Uses simple prompt engineering to reformulate the question with the most relevant documents found in step (2) as context, and sends it to the LLM, returning its answer to the user. The services used by our demo are: Google Gemini API for the LLM and embedding model. Weaviate for a locally-hosted vector DB; Weaviate is an open-source vector database implemented in Go. Google Gemini API for the LLM and embedding model. Google Gemini API Weaviate for a locally-hosted vector DB; Weaviate is an open-source vector database implemented in Go . Weaviate implemented in Go It should be very simple to replace these by other, equivalent services. In fact, this is what the second and third variants of the server are all about! We’ll start with the first variant which uses these tools directly. Using the Gemini API and Weaviate directly Both the Gemini API and Weaviate have convenient Go SDKs (client libraries), and our first server variant uses these directly. The full code of this variant is in this directory . in this directory We won’t reproduce the entire code in this blog post, but here are some notes to keep in mind while reading it: Structure : the code structure will be familiar to anyone who’s written an HTTP server in Go. Client libraries for Gemini and for Weaviate are initialized and the clients are stored in a state value that’s passed to HTTP handlers. Structure Route registration : the HTTP routes for our server are trivial to set up using the routing enhancements introduced in Go 1.22: Route registration routing enhancements mux := http.NewServeMux()
mux.HandleFunc("POST /add/", server.addDocumentsHandler)
mux.HandleFunc("POST /query/", server.queryHandler) mux := http.NewServeMux()
mux.HandleFunc("POST /add/", server.addDocumentsHandler)
mux.HandleFunc("POST /query/", server.queryHandler) Concurrency : the HTTP handlers of our server reach out to other services over the network and wait for a response. This isn’t a problem for Go, since each HTTP handler runs concurrently in its own goroutine. This RAG server can handle a large number of concurrent requests, and the code of each handler is linear and synchronous. Concurrency Batch APIs : since an /add/ request may provide a large number of documents to add to the knowledge base, the server leverages batch APIs for both embeddings ( embModel.BatchEmbedContents ) and the Weaviate DB ( rs.wvClient.Batch ) for efficiency. Batch APIs /add/ batch APIs embModel.BatchEmbedContents rs.wvClient.Batch Using LangChain for Go Our second RAG server variant uses LangChainGo to accomplish the same task. LangChain is a popular Python framework for building LLM-powered applications. LangChainGo is its Go equivalent. The framework has some tools to build applications out of modular components, and supports many LLM providers and vector databases in a common API. This allows developers to write code that may work with any provider and change providers very easily. LangChain LangChainGo The full code for this variant is in this directory . You’ll notice two things when reading the code: in this directory First, it’s somewhat shorter than the previous variant. LangChainGo takes care of wrapping the full APIs of vector databases in common interfaces, and less code is needed to initialize and deal with Weaviate. Second, the LangChainGo API makes it fairly easy to switch providers. Let’s say we want to replace Weaviate by another vector DB; in our previous variant, we’d have to rewrite all the code interfacing the vector DB to use a new API. With a framework like LangChainGo, we no longer need to do so. As long as LangChainGo supports the new vector DB we’re interested in, we should be able to replace just a few lines of code in our server, since all the DBs implement a common interface : common interface type VectorStore interface {
    AddDocuments(ctx context.Context, docs []schema.Document, options ...Option) ([]string, error)
    SimilaritySearch(ctx context.Context, query string, numDocuments int, options ...Option) ([]schema.Document, error)
} type VectorStore interface {
    AddDocuments(ctx context.Context, docs []schema.Document, options ...Option) ([]string, error)
    SimilaritySearch(ctx context.Context, query string, numDocuments int, options ...Option) ([]schema.Document, error)
} Using Genkit for Go Earlier this year, Google introduced Genkit for Go - a new open-source framework for building LLM-powered applications. Genkit shares some characteristics with LangChain, but diverges in other aspects. Genkit for Go Like LangChain, it provides common interfaces that may be implemented by different providers (as plugins), and thus makes switching from one to the other simpler. However, it doesn’t try to prescribe how different LLM components interact; instead, it focuses on production features like prompt management and engineering, and deployment with integrated developer tooling. Our third RAG server variant uses Genkit for Go to accomplish the same task. Its full code is in this directory . in this directory This variant is fairly similar to the LangChainGo one - common interfaces for LLMs, embedders and vector DBs are used instead of direct provider APIs, making it easier to switch from one to another. In addition, deploying an LLM-powered application to production is much easier with Genkit; we don’t implement this in our variant, but feel free to read the documentation if you’re interested. the documentation Summary - Go for LLM-powered applications The samples in this post provide just a taste of what’s possible for building LLM-powered applications in Go. It demonstrates how simple it is to build a powerful RAG server with relatively little code; most important, the samples pack a significant degree of production readiness because of some fundamental Go features. Working with LLM services often means sending REST or RPC requests to a network service, waiting for the response, sending new requests to other services based on that and so on. Go excels at all of these, providing great tools for managing concurrency and the complexity of juggling network services. In addition, Go’s great performance and reliability as a Cloud-native language makes it a natural choice for implementing the more fundamental building blocks of the LLM ecosystem. For some examples, see projects like Ollama , LocalAI , Weaviate or Milvus . Ollama LocalAI Weaviate Milvus Credits: Eli Bendersky Credits: Eli Bendersky Photo by Verne Ho on Unsplash Photo by Verne Ho on Unsplash Verne Ho Unsplash This article is available on The Go Blog under a CC BY 4.0 DEED license. This article is available on The Go Blog under a CC BY 4.0 DEED license. The Go Blog The Go Blog

How to Build LLM-Powered Applications Using Go

Decoding the Invisible Rules That Almost Derailed My 8-Figure Exit There I was, standing outside a downtown office building, clutching a presentation I’d spent weeks perfecting. My hands were clammy. My heart was racing. In just minutes, I’d be pitching my vision for an AI-powered anthropological research platform to a roomful of executives who probably had a dozen other meetings that day. Looking back, I realize that moment wasn’t just about landing a potential client. It was about seeking validation that my idea — and by extension, I — was worthy of taking up space in the business world. When Rejection Becomes Redirection When Rejection Becomes Redirection I might never have been in that boardroom if not for Jay Goldman. When I first shared my vision for bringing anthropological research into corporate decision-making, Jay could have nodded politely and moved on with his day. Instead, he truly listened. He connected me with his then CEO, who then offered me the chance to pitch their board — a priceless opportunity for someone with just an idea and determination. Jay Goldman The meeting itself was anything but sterile. The team engaged thoughtfully, asking insightful questions and giving my presentation their genuine attention. Their feedback was measured and considered. While they ultimately decided my solution wasn’t the right fit for their current direction, they took the time to acknowledge the merit in my approach. “Your idea has real potential,” they said. “It may not align with our focus right now, but there’s definitely something valuable here worth pursuing.” Those words of validation, coming from seasoned executives who had no obligation to encourage me, became the foundation for what would eventually grow into MotivBase and lead to a 10x ARR exit years later. What made the difference? Why did this moment of redirection become fuel rather than a full stop? Here’s what I’ve come to understand after years of studying human behavior as an anthropologist and living the entrepreneurial rollercoaster: Our ideas about success aren’t really our own. We unconsciously absorb messages about who has the right to succeed and how that success should happen. I call these “invisible rules” — unwritten codes that silently determine what paths are considered legitimate. For me and my co-founder Jason Partridge, we had internalized the belief that legitimate startups need substantial funding, fancy offices, and institutional backing. We couldn’t even imagine bootstrapping because that path didn’t exist in our mental model of “real” entrepreneurship. Jason Partridge It took another pivotal conversation — this time with Harvey Carroll, who was at IPG Mediabrands at the time — to challenge that limiting belief. While we were busy explaining how we needed financial backing to launch properly, Harvey cut through our assumptions with simple clarity: “What’s stopping you from just doing this yourselves? What’s the worst that’s going to happen? You’ll lose a few months of your life. And if you don’t try, you’ll always wonder what could have been.” Harvey Carroll It was as if someone had suddenly handed me glasses that revealed hidden writing on a wall I’d been staring at for years. The Line Between Defeat and Discovery The Line Between Defeat and Discovery This brings me to what I believe is the critical inflection point in any entrepreneurial journey: the fine line between letting rejection define you and letting it refine you. The difference isn’t in the rejection itself. It’s in whether you can recognize that your reaction to that rejection is filtered through invisible rules you’ve unknowingly adopted. When someone says “This won’t work,” are they really saying it’s impossible, or just that it doesn’t fit the conventional template of success?


When you feel unqualified, is it because you truly lack capability, or because you don’t match the profile of who’s “supposed” to succeed in your field?


When you hesitate to start without outside backing, is it because you actually need it, or because you’ve been conditioned to believe that’s the only legitimate path? When someone says “This won’t work,” are they really saying it’s impossible, or just that it doesn’t fit the conventional template of success? When someone says “This won’t work,” are they really saying it’s impossible, or just that it doesn’t fit the conventional template of success? When you feel unqualified, is it because you truly lack capability, or because you don’t match the profile of who’s “supposed” to succeed in your field? When you feel unqualified, is it because you truly lack capability, or because you don’t match the profile of who’s “supposed” to succeed in your field? When you hesitate to start without outside backing, is it because you actually need it, or because you’ve been conditioned to believe that’s the only legitimate path? When you hesitate to start without outside backing, is it because you actually need it, or because you’ve been conditioned to believe that’s the only legitimate path? The most profound insight from my journey wasn’t learning to bounce back from rejection — it was recognizing how many of my limitations were self-imposed because I had internalized rules created by and for a system designed to work for the 1%, not the 99% of entrepreneurs. The most profound insight from my journey wasn’t learning to bounce back from rejection — it was recognizing how many of my limitations were self-imposed because I had internalized rules created by and for a system designed to work for the 1%, not the 99% of entrepreneurs. The most profound insight from my journey wasn’t learning to bounce back from rejection — it was recognizing how many of my limitations were self-imposed because I had internalized rules created by and for a system designed to work for the 1%, not the 99% of entrepreneurs. Breaking Rules You Didn’t Know Existed Breaking Rules You Didn’t Know Existed The day after that conversation with Harvey, my co-founder and I called our lawyers to incorporate. Not because we suddenly had funding or a clear roadmap, but because we finally had permission — from ourselves — to try. We decided to bootstrap what would eventually become MotivBase, even though it went against everything we thought was required for “legitimate” success. We chose sustainable growth over hypergrowth, focusing on building something meaningful rather than chasing vanity metrics. It wasn’t easy. We didn’t have the safety net of venture capital. But what we gained was immeasurable: the freedom to build a business aligned with our values rather than external expectations. Today, as I work with founders at various stages of building their businesses, I see the same patterns playing out. Brilliant entrepreneurs who doubt themselves not because they lack ability, but because they don’t fit the mold of who’s “supposed to” succeed. My message to them is the same message I wish I’d understood earlier: The most powerful decision you’ll ever make isn’t what business to start — it’s choosing which rules to follow and which to rewrite. When you can see the unwritten rulebook that’s been silently guiding your decisions, you can finally make conscious choices about your path forward. You can build success on your terms, not someone else’s template. And sometimes, all it takes is one person — like Jay or Harvey was for me — who believes in you enough to help you see past those invisible boundaries. Their generosity with their time, their willingness to listen, and their honest feedback didn’t just open doors — they helped me see that rejection isn’t always about your idea’s merit, but about how it fits into a system built for a very specific type of success. As I work on my upcoming book, “Mastering the Invisible Rulebook,” I’m constantly reminded of how these hidden dynamics shape not just individual careers but entire industries — determining who gets funded, whose ideas get green-lit, and what kinds of companies thrive. The journey from that nervous pitch to exit wasn’t just about building a company. It was about recognizing that success isn’t a one-size-fits-all destination with a single prescribed path. It’s about having the courage to question the rules and, when necessary, write new ones. What invisible rule have you internalized that might be limiting your vision of what’s possible? When has rejection actually redirected you toward something better aligned with your authentic path? I’d love to hear your stories as I continue sharing mine. Want early access to my book? Join the Inner Circle Join the Inner Circle

What If the Only Thing Holding You Back Is an Invisible Rule You Never Questioned?

እርስዎን ለመጠበቅ ብቻ ነገር እርስዎም ምንም ጊዜ የሚፈልጉት የማይታወቁ ሁኔታ ነው?

¿Y si la única cosa que te mantiene atrás es una regla invisible que nunca preguntaste?

क्या होगा अगर एकमात्र चीज जो आपको वापस रखती है वह एक अदृश्य नियम है जिसे आपने कभी नहीं पूछा था?

もしあなたを支える唯一のものは、あなたが決して尋ねなかった見えないルールだったら?

Ką daryti, jei vienintelis dalykas, kuris jus sulaiko, yra nematoma taisyklė, apie kurią niekada neklausėte?

Ko darīt, ja vienīgā lieta, kas jūs tur atpakaļ, ir neredzams noteikums, kuru jūs nekad neesat jautājuši?

Co by było, gdyby jedyną rzeczą, która cię powstrzymała, była niewidzialna reguła, o którą nigdy nie pytałeś?

که یوازې هغه څه چې تاسو ته ډډه کوي دا یو نامتو قواعد دی چې تاسو هیڅکله پوښتنه نلري؟

E se a única coisa que o mantém de volta é uma regra invisível que você nunca perguntou?

ඔබ ආපසු තබා ඇති එකම දෙය ඔබ කවදාවත් ප්රශ්නය නොකළ අසාමාන්ය නීතිය නම් කුමක්ද?

Čo ak jediná vec, ktorá vás drží späť, je neviditeľné pravidlo, o ktoré ste sa nikdy nepýtal?

Yintoni ukuba into elinye enikezela umyalelo olungabonakali ukuba awukwazi ukufumana?

Ethereum Is More Than Crypto. It’s a Machine for Making Worlds

Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 2 Methodology 2 Methodology 3 Hardware 3 Hardware 4 Software 4 Software 5 Network 5 Network 6 Consensus 6 Consensus 7 Cryptocurrency Economics 7 Cryptocurrency Economics 8 Client API 8 Client API 9 Governance 9 Governance 10 Geography 10 Geography 11 Case Studies 11 Case Studies 12 Discussion and References 12 Discussion and References A. Decentralization and Policymaking A. Decentralization and Policymaking B. Software Testing B. Software Testing C. Brief Evaluations per Layer C. Brief Evaluations per Layer D. Measuring decentralization D. Measuring decentralization E. Fault Tolerance and Decentralization E. Fault Tolerance and Decentralization 6 Consensus Protocols like Bitcoin [78], Algorand [40], or Ouroboros Praos [78], enable resource holders to engage in the protocol directly with (essentially) whatever amount of resources they have. In these protocols, block producers can, even though they do not have to, form coalitions called pools. In PoW, a pool “leader” validates transactions, and organizes them in a candidate block, while each “member” executes the PoW puzzle for the leader-made block. If a member is successful, the leader collects the block’s reward and distributes it, proportionately to each member’s power. In PoS, the leader has full control over the block’s creation, while the members only pay fees to delegate their staking rights to the leader and collect rewards. Pooling behavior is also driven by temporal discounting [146], i.e., the tendency to disfavor rare or delayed rewards. In essence, a small miner may prefer small frequent payments, at the cost of some fee, over rare large payments, when producing a block. Other systems, like Cosmos [114] and EOS [92], impose restrictions on which parties can participate in consensus and require the rest to delegate their resources to a representative or “validator” node. This “barrier to entry” means that any party without enough stake, i.e., below the system’s threshold or less than its competitors, is required to delegate their staking rights to a validator. At every “epoch”, a committee of (a fixed number of) parties is elected to run the protocol. The election mechanism is voting-based, with resource delegation acting as the voting process. In both types of systems, there are two resources of interest: i) owned participating power, e.g., computational or stake; ii) delegated participating power, including the power to choose a block’s content. Accordingly, the relevant parties are: i) miners and stakeholders, who own hashing power and stake respectively; ii) pool leaders and delegates, who control how the resources are used. Typically, the security of a ledger is guaranteed if the parties that represent an aggregate majority of the participating power are honest (i.e., they follow the protocol as prescribed) [78]. Therefore, the concentration of participating power around few entities poses a threat to the system. This hazard is well-known and blockchain users and participants have actively tried to avoid it since at least 2014 [86]. Those controlling a power majority can hurt liveness, by refusing to publish or accept certain transactions, as well as safety by launching a long-range attack. Both types of attacks also indirectly hurt stability, since the system’s trustworthiness is challenged. A second concern revolves around block proposers. A proposer is a party that maintains a mempool and chooses which transactions are added to a block and in what order. Initially, a single party acted as both block proposer and builder. With the increase in hardware requirements needed to run a full node and the formation of pools, the two roles of proposer and builder were separated. In PoW ledgers, the leader of the pool typically proposes the block’s content, whereas the pool members only run the PoW algorithm. Therefore, pool members are not involved in a block’s construction and often do not even validate its contents. Therefore, the leader may censor transactions (liveness hazard), steal member rewards (stability hazard), or possibly link the user’s resources with information like IP addresses (privacy hazard). In addition, smart contracts enable MEV-type attacks [186], which might hurt stability. Here, block builders have the ability to observe transactions before publication and choose their order in a block, which they can exploit to extract value from honest transactions. A countermeasure that has been introduced is the proposer-builder separation (PBS) model, wherein a trusted party maintains a mempool and proposes a block, whereas validators sign it without ever observing its content (thus not being able to exploit its MEV) [33]. Still, the current implementation of PBS in Ethereum has been criticized for facilitating censorship and centralization, hence its usefulness remains unclear [88]. Finally, a threat arises due to the lack of self-healing, i.e., the inability to recover from a temporary adversarial takeover. In PoW, even if a majority gets corrupted, honest users can increase their own power and, eventually, overthrow the adversary and restore the ledger’s security [10,13]. In PoS though, power shift takes place on the ledger, by transferring stake. If an adversary temporarily obtains a majority, they can prohibit transactions that shift power away from them, thus retaining control indefinitely (for example, a large centralized cryptocurrency exchange can make it hard to issue outgoing payments and withdrawals, while enabling payments between different users of the exchange). Consequently, a diverse stake distribution (cf. Section 7) is vital to protect against takeovers. Authors:
(1) Christina Ovezik, University of Edinburgh (c.ovezik@ed.ac.uk);
(2) Dimitris Karakostas, University of Edinburgh (dkarakos@ed.ac.uk);
(3) Aggelos Kiayias, University of Edinburgh and IOG (akiayias@ed.ac.uk). Authors: Authors: (1) Christina Ovezik, University of Edinburgh (c.ovezik@ed.ac.uk); (2) Dimitris Karakostas, University of Edinburgh (dkarakos@ed.ac.uk); (3) Aggelos Kiayias, University of Edinburgh and IOG (akiayias@ed.ac.uk). This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv available on arxiv

Can Blockchain Stay Fair for the Long Haul?

Digital Dollars, Digital Yuan, Digital Chaos? The CBDC Arms Race Explained

Cybercriminals are now attacking larger organizations for bigger payouts. With ransom demands doubling between the first and fourth quarters of 2022, as demonstrated in Fig 1, they currently exceed $1 million, making it crucial for enterprises to bolster their defenses. Notably, this trend where larger organizations are getting targeted for higher ransoms by attackers comes when these firms have increased their reliance on remote work, digitalized control, and cloud-based operations, adopting lessons learned during the COVID-19 pandemic. However, there are various steps you can take to safeguard your organization from this growing cybersecurity threat. They include employee training and awareness, data backups, regular software and application updates, antimalware software, network segmentation, optimized email protections, application allowlisting, access protection, and regular penetration testing. How to Safeguard Your Organization Against Ransomware Attacks How to Safeguard Your Organization Against Ransomware Attacks Employee Training and Awareness Employee Training and Awareness The first step in safeguarding your organization against ransomware attacks is employee training. All workers must understand ransomware attacks as part of their cybersecurity awareness campaigns. Make sure to enlist the assistance of renowned organizational cybersecurity companies to engage in both online and physical training. Employees must know and understand the risk points, ransomware response frameworks, developments in ransomware attacks, and how to react to suspicious online and offline activity. Proper training and awareness ensure your organization and its employees are ready for attacks. Backup All Critical Data Backup All Critical Data Backing up all critical data using the 3-2-1 methodology protects an organization's data against attackers, making recovery from attacks easier and faster. The 3-2-1 methodology entails saving all critical organizational data as three separate copies in two different types of data storage and ensuring one copy is always offline and air-gaped. Consider using high-tech, solid-state, large-capacity portable hard disks with encryption capabilities for offline storage. Also, cloud-based storage complements hard disks, and I am considering working with reputable companies like Amazon Web Services (AWS), Egnyte Business Storage, and Tresorit Business Cloud Storage. Always prescribe for business packages when dealing with cloud storage options because they have higher security functionalities and offer high-capacity, immutable storage. Keep all Software, User Passwords, and Systems Updated Keep all Software, User Passwords, and Systems Updated Various malware like viruses and ransomware evolve to evade aging cybersecurity systems and software. Therefore, you should continuously update your systems to the latest version to benefit from in-built cybersecurity features. Also, an organization elevates its ransomware protection by updating its software regularly to keep abreast of ransomware mutations. The 2017 WannaCry ransomware attack, which crippled the UK's healthcare infrastructure, Spanish telecoms giant Telefonica, and Taiwanese tech giant TSMC was caused by laxity in updating cybersecurity software and the Microsoft operating systems. User Passwords are common access points through which ransomware makes its way into organizational networks that rely on remote access. According to socradar.io, up to 21% of all ransomware attacks in 2020 were attributable to weak passwords in the access management systems of organizations, as demonstrated in the infographic in Fig 2. Therefore, one must consider teaching password management practices like creating long, multi-symbolic alphanumeric passwords that can only be used for a limited period. If the user fails to update their password, they are locked out of the system. After creating a new, similarly strong password, they must utilize multiple-factor authentication to access the network. Phishing attacks rely on weak passwords and other reckless practices in weak access management systems. Also, combining biometric information with card-based passwords makes cards useless when their verifiable owners are absent. socradar.io Install and Use Renowned Firewalls and Antivirus Software Install and Use Renowned Firewalls and Antivirus Software Firewalls are the first defense against attacks targeting online software and hardware. It would help if you sourced the latest firewalls from reputable companies like Sophos, pfSense, and FortiGate. Always seek firewalls designed for business applications because they have advanced ransomware defense capabilities. Also, VPN-specific ransomware detection functionalities should be included to protect businesses that rely on remote access operations and cloud-based storage. Combine high-level firewalls with reputable antivirus software for enterprises like Norton, ESET, and Bitdefender. The IT technicians serving your company or organization must set these two levels of ransomware defenses to scan the entire system daily. Weekly full system scans are advisable as they take longer and may interrupt operations. Segment Your Network Segment Your Network Network segmentation entails dividing the organization’s operational environment and infrastructure into smaller tiers or sub-networks that are wholly isolated but work in coordination. This ransomware mitigation strategy aims to reduce the access and damage attacks can render to the organization. Ransomware attacks rely on network integration to spread from their entry point into other hardware and software components. Network segmentation isolates the malware to certain levels of the organization’s systems and infrastructure, reducing damage and improving recovery from the attack. One of the best implementations of network segmentation is physical architecture, where individual hardware items are maintained in separate subnets. However, physical architecture may limit operational efficiency due to the difficulty of remotely managing the isolated physical components. Physical segmentation may incorporate static IP addresses and advanced features at the levels of switches and routers to isolate external access attempts. An emerging trend in organizational protection is intent-based segmentation, where network semantics dictate why the network has segmented itself from the central system. This form of network segregation benefits small and more significant business organizations with additional security features like zero-trust network principles. This segmentation approach is also essential in organizations with discrete operations that rely on need-to-know data requiring higher security levels, even from internal operators. Micro-segmentation is also taking off as an advanced form of network segmentation that incorporates virtual local area networks (VLANs) and access control lists to dictate segment access in conjunction with intent-based protocols. Update Email Protections Update Email Protections Emails are integral to how ransomware accesses business organizations through downloadable suspicious email attachments, links to infected software, and social engineering. According to the Federal Bureau of Investigations (FBI), emails are the leading entry methods for ransomware into business organizations, accounting for more than 54% of all ransomware attacks in 2020. Therefore, consider updating the organization's email protections to protect yourself from email risk points. First, employees should never open emails from unknown senders. This includes clicking on the email’s bodies, and they should report such emails immediately to the IT department personnel and management. Secondly, constantly update client email applications to benefit from high-level cybersecurity features. Thirdly, establish Sender Policy Frameworks (SPFs), which entail designating specific servers from which client emails can only come for additional security. Fourth, establish DomainKeys Identified Mail (DKIM), which involves digital signatures and an encryption key for emails from verified and known senders. Finally, email protection must include Domain Message Authentication, Reporting, and Conformance (DMARC), which combines SPF and DKIM functionalities in a dynamic package, as demonstrated below in Fig 3. Application Whitelisting Application Whitelisting Application whitelisting is a network security feature that designates which applications a network can download, open, and use in its functionalities and infrastructure. Malware ordinarily piggybacks on legitimate applications, imitating appearance, authentication, and functionalities. Other malware used in ransomware attacks utilize macros to trick unsuspecting or reckless organizational personnel into downloading trojans and viruses by hiding in MS Word documents. Whitelisting prevents such malware from executing through advanced detection processes. Ransomware morphs at a very rapid rate to avoid detection and imitate various legitimate applications. However, regardless of how fast such malware morphs to avoid detection, if it is not on the application whitelist serving the network’s cybersecurity purposes, it cannot gain access to data or systems. Applications whitelisting best practices dictate that whitelisted applications gain access to the network using zero-trust architecture. Also, only authorized network administrators who require access to such applications and network sections or functionalities are allowed to use such applications on the network. One of the most common whitelisting apps is Windows AppLocker, which could enable the user to benefit from additional Microsoft ransomware detection and management functionalities. End-User Device and Access Privilege Protections End-User Device and Access Privilege Protections End-user protection during ransomware mitigation entails detection and authenticating end-user access to protected networks. Herein, your organization must be able to detect all forms of access, whether through laptops, smartphones, tablets, flash disks, or hard drives, physically or remotely. Consider employing advanced End Point Detection and Response (EDR) services and applications like Bitdefender EDR and Cisco Advanced Malware Protection for Endpoints in your organization, as they provide continuous monitoring, detection, and response to network access and suspicious hardware or software activities. Standard EDR tools combine antimalware, data encryption, intrusion detection, mobile and desktop security, and web browser security with real-time notification and alert functionalities. Notably, least privilege strategies of access management can also contribute to safeguarding your organization against ransomware attacks. This strategy entails providing authenticated and verified users on the network with only access and data necessary to perform predetermined activities. Also, the Role-Based Access Control (RBAC) policy helps prevent ransomware through access and end-user management. Only verified users with specific roles are granted access to data and systems relevant to their intended and reported activities in the network. These strategies for access control are complemented by multi-factor authentication (MFA) and zero-trust architecture. Regular Intrusion and Readiness Testing Regular Intrusion and Readiness Testing Regular intrusion and readiness testing is the final safeguard against ransomware attacks. This strategy entails simulating breaches using various known and cutting-edge ransomware strategies in discrete and random tests to test personnel readiness, system preparedness, and mitigation strategy performance. In addition, organizations must consider regularly re-evaluating access points and user privileges, identifying new or mutated system vulnerabilities, and creating new security protocols in keeping with the best industry standards. Regular intrusion and readiness testing also involves retraining all organizational personnel on common points of risk like regular password changing with solid alternatives, safe web surfing, and browsing, implementation of robust VPNs by avoiding public Wi-Fi zones, and recognition of suspicious and malicious files or online content. The organization must also regularly train its personnel on the most up-to-date social engineering practices. It is best practice to engage renowned organizational cybersecurity firms periodically in training and retraining activities to understand the developments and needs of the firm fully. Conclusion In conclusion, ransomware attacks are increasingly growing and targeting larger organizations in what is now known as 'big fish hunting.' The frequency of such cyberattacks is increasing, as are the ransom amounts demanded by the attacks. This unfortunate cybersecurity trend coincides with the post-COVID-19 pandemic, where most medium and large organizations have adopted additional online functionalities and embraced remote working. However, you can safeguard your organization from ransomware through employee training and awareness, data backups, regular software and application updates, antimalware software, network segmentation, optimized email protections, application whitelisting, access protection, and regular penetration testing. References References https://www.coveware.com/blog/2023/4/28/big-game-hunting-is-back-despite-decreasing-ransom-payment-amounts
https://www.kaspersky.com/resource-center/threats/ransomware-wannacry
https://socradar.io/top-five-causes-of-ransomware-attacks/
https://www.cisco.com/c/en/us/solutions/collateral/enterprise-networks/enterprise-network-security/intent-based-network-security-aag.html#:~:text=Intent-based network security is,the distributed network it exists.
https://www.fbi.gov/news/press-releases/fbi-releases-the-internet-crime-complaint-center-2020-internet-crime-report-including-covid-19-scam-statistics
https://blog.mdaemon.com/dmarc-best-practices-securing-your-email-communications
https://learn.microsoft.com/en-us/defender-endpoint/malware/macro-malware
https://www.digitalguardian.com/blog/what-role-based-access-control-rbac-examples-benefits-and-more https://www.coveware.com/blog/2023/4/28/big-game-hunting-is-back-despite-decreasing-ransom-payment-amounts https://www.coveware.com/blog/2023/4/28/big-game-hunting-is-back-despite-decreasing-ransom-payment-amounts https://www.kaspersky.com/resource-center/threats/ransomware-wannacry https://www.kaspersky.com/resource-center/threats/ransomware-wannacry https://socradar.io/top-five-causes-of-ransomware-attacks/ https://socradar.io/top-five-causes-of-ransomware-attacks/ https://www.cisco.com/c/en/us/solutions/collateral/enterprise-networks/enterprise-network-security/intent-based-network-security-aag.html#:~:text=Intent-based network security is,the distributed network it exists. https://www.cisco.com/c/en/us/solutions/collateral/enterprise-networks/enterprise-network-security/intent-based-network-security-aag.html#:~:text=Intent-based network security is,the distributed network it exists https://www.fbi.gov/news/press-releases/fbi-releases-the-internet-crime-complaint-center-2020-internet-crime-report-including-covid-19-scam-statistics https://www.fbi.gov/news/press-releases/fbi-releases-the-internet-crime-complaint-center-2020-internet-crime-report-including-covid-19-scam-statistics https://blog.mdaemon.com/dmarc-best-practices-securing-your-email-communications https://blog.mdaemon.com/dmarc-best-practices-securing-your-email-communications https://learn.microsoft.com/en-us/defender-endpoint/malware/macro-malware https://learn.microsoft.com/en-us/defender-endpoint/malware/macro-malware https://www.digitalguardian.com/blog/what-role-based-access-control-rbac-examples-benefits-and-more https://www.digitalguardian.com/blog/what-role-based-access-control-rbac-examples-benefits-and-more

The High Stakes of Big Game Hunting in Cybersecurity

In recent years, artificial intelligence (AI) has become an essential part of many industries, with health care being no exception. Its ability to enhance practices, streamline processes and provide real-time insights is reshaping the way care facilities operate. But how does AI improve patient safety in hospitals? Enhancing Surgical Precision with AI Enhancing Surgical Precision with AI Enhancing Surgical Precision with AI All surgical procedures require an incredibly high level of precision because even the smallest error can lead to complications. Although surgeons are highly trained professionals, they can benefit from technological assistance to enhance their accuracy and decision-making during difficult surgeries. AI video analytics is emerging as a vital tool in improving surgeries. Automated video systems can analyze live feeds of the surgical area, offering guidance to the surgical team throughout the procedure. By using advanced image recognition and machine learning algorithms, these systems can highlight critical areas of focus like tissue differentiation and even surgical tool positioning. live feeds of the surgical area live feeds of the surgical area AI can also track the team’s movements, identifying any deviations from optimal techniques or patterns. This feedback loop can help them correct any potential mistakes before they escalate, enhancing the overall precision of the operation. can also track the team’s movements can also track the team’s movements In high-stakes surgeries, AI video analytics offers an extra layer of support, providing objective analysis and real-time feedback to ensure only the most favorable outcomes. This boosts patient safety and may offer shorter recovery times and better overall outcomes. The Role of AI Video in Monitoring Sedation Levels The Role of AI Video in Monitoring Sedation Levels The Role of AI Video in Monitoring Sedation Levels The Role of AI Video in Monitoring Sedation Levels Both over- and under-sedation can lead to serious complications, including respiratory distress or waking up during surgery. Monitoring the medication’s delivery is critical for operations that require general anesthesia. Not only does it come with more risks, but it’s necessary for more intensive procedures, and waking up during these can be very dangerous. can lead to serious complications can lead to serious complications Traditionally, clinicians rely on various tools and their own observations to assess a patient’s sedation status. However, these methods can sometimes be subjective or prone to human error. AI-powered video monitoring is making waves in this area. By tracking subtle facial cues like blink rate, pupil dilation and facial muscle movement, AI systems can provide data on a patient’s sedation. They analyze video feeds and use algorithms to detect signs of over- or under-sedation. For instance, a decrease in blink rate could indicate a patient is too deeply sedated, while rapid blinking or facial tension may signal insufficient sedation. can provide data on can provide data on If the system detects irregularities in sedation, alerts can be sent to the medical team so they’re able to correct the issue. This makes it possible for clinicians to adjust sedation levels quickly and reduce the risk of complications. AI in Post-Surgery and Recovery AI in Post-Surgery and Recovery AI in Post-Surgery and Recovery AI in Post-Surgery and Recovery The period following surgery is essential for a patient’s recovery because it involves careful monitoring to ensure no complications occur. It is also important to ensure the healing process goes smoothly. Traditionally, post-surgery recovery relies on routine check-ups and patient self-reporting, but AI video analytics is now making this process more efficient and accurate. AI systems can now monitor patients during recovery by tracking their movements, alertness and overall well-being. For instance, video analysis can detect if a patient is attempting to get out of bed too early, which could lead to falls or injury. By analyzing facial expressions and body language, the system can also identify signs of pain or discomfort that might otherwise go unnoticed, which allows medical staff to respond more quickly to a patient’s needs. Automation technology can also monitor key recovery indicators like respiratory patterns or heart rate through video feeds. These can alert the medical team to irregularities like changes in breathing or excessive movement, which might indicate the need for intervention. can also monitor key recovery indicators can also monitor key recovery indicators AI-powered video can help track post-surgical physical therapy progress. For example, it can ensure patients are following the prescribed rehabilitation exercises, providing feedback to both them and clinicians. It can also measure the range of motion or symmetry in movements to support recovery efforts and prevent setbacks. Using AI in post-surgery care can help hospitals ensure faster, more accurate recovery monitoring, reducing complications and improving overall patient outcomes. are following the prescribed rehabilitation exercises are following the prescribed rehabilitation exercises Reducing Human Error and Improving Patient Care Reducing Human Error and Improving Patient Care Reducing Human Error and Improving Patient Care Reducing Human Error and Improving Patient Care Even the most skilled professionals are susceptible to human error, especially when exposed to high-stress environments like operating theatres. Fatigue, distractions, and the volume of patients can lead to mistakes in monitoring, medication administration and patient assessments. AI video analytics help reduce these errors by providing an extra layer of oversight and alerts that support decision-making. One of the largest areas where AI minimizes human error is in medication management. Automated systems can monitor whether the correct dosages and types of medication are being administered to ensure nurses or pharmacists follow proper protocols. This can be particularly useful in preventing dosage miscalculations. correct dosages and types of medication correct dosages and types of medication AI video also enhances patient safety by ensuring compliance with hospital hygiene protocols. Hand hygiene is one of the simplest factors in preventing further medical issues. AI-driven video monitoring can track whether health care workers sanitize their hands before and after patient interactions, reducing the risk of hospital-acquired infections. sanitize their hands before and after sanitize their hands before and after Strengthening Hospital Security Strengthening Hospital Security Strengthening Hospital Security Strengthening Hospital Security Hospitals are high-traffic environments where security challenges are constant. From unauthorized access to missing medical equipment, maintaining a safe and secure facility is essential for both patients and staff. Traditional security measures like CCTV cameras and on-site security personnel have limitations. AI-powered video surveillance enhances hospital security by providing real-time monitoring, automated alerts and predictive threat detection. by providing real-time monitoring by providing real-time monitoring One of the biggest advantages of AI-driven security is its ability to detect unusual behavior before it escalates into a security threat. Video analytics can identify loitering, unauthorized access or even the presence of concealed weapons. Unlike traditional security cameras, it analyzes video feeds continuously, flagging potential threats instantly so hospital security teams can respond faster. AI vision can also improve access control by integrating facial recognition and badge verification systems. This ensures only authorized personnel enter restricted zones like operating rooms, ICUs and pharmaceutical storage areas. It can also track visitors, logging their movements to prevent security breaches or unauthorized patient interactions. by integrating facial recognition by integrating facial recognition Another critical security challenge in hospitals is asset protection. Expensive medical equipment can get misplaced or stolen in the field, either through innocent or malicious means. AI-powered surveillance can track these assets using object recognition, ensuring essential tools are always available when necessary. can get misplaced or stolen can get misplaced or stolen Such video systems also play a role in emergency response. If a patient or visitor collapses, AI can instantly detect the fall and alert nearby medical staff. In cases of violence or distress, AI-driven cameras can identify escalating situations and notify security before they get out of control. Using automation for video surveillance can significantly enhance hospitals’ security infrastructure, ensuring a safer environment for patients, staff and visitors. How Does AI Improve Patient Safety in Hospitals? AI-powered video monitoring is transforming hospital safety in once-unimaginable ways. From ensuring patients receive the right level of sedation to enhancing surgical precision, supporting post-op recovery and tightening hospital security, AI is proving to be an invaluable tool in modern health care. As hospitals continue to evolve, automation-driven video technology will play an even greater role in keeping patients safe, streamlining operations and preventing potential crises before they unfold. In an environment where every second counts, having an extra set of “eyes” that never blink can make all the difference.

Hospitals Are Now Considering Using AI to Keep Patients Safe

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