Peter E.'s Linkedin Analytics

Small businesses think they’re too small to be targeted. But... ➝ 43% of cyberattacks attack small businesses. ➝ 60% of SMEs go out of business within 6 months after a major breach. In the US: 👉 4,500 cyber attacks on SMEs happen daily! 👉 Over 1.6 million attacks on small businesses, annually. But the truth is: SMEs don't have the right resources, tools, or expertise to tackle cyber threats. And cybercriminals know it. That's why they're hit the hardest. So, what can SMEs do to protect themselves? Here are the 3 high-level strategies I recommend: 1. Implement Zero Trust Architecture: Don’t trust anything by default, even internal network users. Verify every access request every time. 2 .Use Endpoint Detection and Response (EDR): Equip every device with advanced monitoring tools to detect and respond to threats in real time. 3 . Create a Robust Incident Response Plan: Be prepared.  Your team needs a proven, tested strategy to contain, recover, and prevent future breaches. And the time to act is NOW. Repost ♻️ to spread the word in your network.

I’m not here to tell you that AI is the future. I’m here to tell you that AI is already transforming businesses. Here is why I believe it: For years, IBM has been on a mission to embed AI into every layer of its operations, from hybrid cloud solutions to quantum computing. IBM’s CEO, Arvind Krishna, put it best: “The companies that will outperform in the next decade will truly be AI-first.” And this is already happening. IBM’s Granite 3.0 models are a perfect example. They are designed to deliver real ROI for businesses of all scales. AI and cloud tech can level the playing field, letting small businesses operate with enterprise efficiency That’s the kind of innovation I live for—practical, responsible, and built to grow with you. Back when I was running my web design agency, I saw small businesses need solutions that work. I hit rock bottom once, drowning in broken systems and client disappointments. But that’s when I realized that AI, automation, and cloud tech could’ve saved me years of headaches. Now, with platforms like ComputeSphere I’m helping others skip that struggle and scale like enterprises. AI is not some distant dream for the Fortune 500. It is here, and it’s for us entrepreneurs, dreamers, and doers, at any level, who want growth. PS: How are you using AI to scale your business? Drop your thoughts below I’d love to swap ideas!

You're not invisible at all, SMBs! It doesn't matter if you are a Fortune 500 company or a solo entrepreneur, Cyber attackers are coming for you. Most small business think they are safe. That their business is not on the radar of hackers and attackers. But the truth is no one is invisible. Hackers will exploit a misconfigured server, an unpatched app, or even a team member’s recycled password. But you don’t have to be their easy win. → Encrypt your sensitive files locally first.  Zip sensitive data with 7-Zip and a password before uploading. Hackers hit a dead end even if they breach your storage. → Adopt DNS filtering Block malicious domains with OpenDNS (Cisco’s free tier works). CISA.gov cites this as a top defense layer. → Avoid giving your contact emails Grab a free temporary email like Temp-Mail for anything sketchy newsletters, trials. It keeps your main inbox off the phishing radar without any extra cost. You can’t eliminate risk completely. But you can absolutely minimize your exposure. The more proactive you are now, the less likely you are to become a target. Repost ♻️ to share it with your network. P.S. What’s the most critical security decision you’ve made for your company this year?

AI can speed up development, but let's not let old vulnerabilities slip back in. I remember when coding meant sitting down with a small team, carefully reviewing the code. Now coding is made easy and faster with the help of AI agents. AI grabs stuff from open-source repositories from places like npm, PyPI, GitHub. Old bugs like CVE-2015-XXXX, are still lurking there unpatched. AI just copies and pastes that into your code. Last month, I saw a big company use AI-made code with a 2018 Apache Struts problem. Hackers got in within 72 hours. Snyk’s 2024 report says 30% of AI-made code has serious bugs from old open-source stuff. AI is making us faster but it’s exposing us to bigger threats. I focus on scaling businesses with AI and cloud, and I’ve learned this: speed means nothing if it’s not secure. You have to balance speed and security. Here’s how I tackle it: → I run Static Application Security Testing (SAST). Tools like Semgrep with AI-tuned rules catch flaws before they sneak into my pipeline. → I build a Software Bill of Materials (SBOM). I check it against NIST’s NVD and ditch any dependency with a CVSS score above 7.0.  → I red-team AI outputs. Every month, I test for weak spots like sloppy encryption that AI often overlooks. → I enforce a zero-trust pipeline. I isolate AI agents and route their code through SecOps for a human double-check. This isn’t cheap or easy. Strong security never is. AI is a force multiplier for you and attackers. Take back the control before they hit your business. Repost ♻️ to share with your network. P.S. What is your strategy for reviewing AI-written code?

AI is not limited to LLMs.  It is part of your daily routine. Everyone is drooling over chatbots like they are the king of AI, but AI is been in your life way before LLMs started typing essays. Take my day as an example: I wake up, and Gmail’s AI has already blocked spam that could’ve wasted my time—saving me 30 minutes right off the bat. I get in the car, and Google Maps reroutes me to avoid traffic, shaving off 20 minutes of drive time. I respond to emails, and Smart Reply handles the quick responses, slashing my reply time from 10 minutes to 2. AI is not just in your tech stack or reserved for data scientists—it is already embedded in the tools you use every day, making your life more efficient and personalized. Google’s AI already blocks 100 million spams daily, and Maps uses real-time data to save us time. Want to see the impact? Start with one tool like Gmail’s spam filter and measure how much time you save. 🔁 Repost if you want others to recognize how AI is shaping our daily lives. P.S. Do you believe AI is underutilized in day-to-day business activities? P.P.S.: Image Credit: Alex Wang

AI’s “Reasoning” hype will flop without cheaper computing... If you think the future of AI will be defined by better algorithms or more data, you are missing the bigger picture. Jensen Huang, CEO of Nvidia, reiterated this recently: “The future of artificial intelligence will be services that can “reason,” but such a stage requires the cost of computing to come down first.” As someone who has spent over 15 years working in cloud computing, I could not agree more. The focus is not just on improving AI capabilities, but on making the infrastructure more accessible. I’m thinking about the infrastructure that will make it possible. Huang’s goal is clear: boost chip performance 2-3x every year, all while maintaining cost and energy efficiency. This is the breakthrough that will transform AI inference—the ability to make conclusions from data and help AI systems process information more intelligently. Affordable computing is the key to the next wave of AI. We have already seen how infrastructure costs in cloud computing can restrict the potential of even the most powerful tech solutions. The hardware is on its way. However, the real power will be in cloud systems that balance performance and affordability. PS: How are you preparing your business to adapt to the upcoming changes in AI and computing? I'd be happy to discuss how you can leverage affordable cloud solutions.

It’s not just SMBs getting overcharged by cloud providers. Restrictive software licenses are driving up cloud costs for government agencies too. A new report from the U.S. Government Accountability Office (GAO) found that software vendors are making it harder and more expensive for federal agencies to move to the cloud. The GAO reviewed six agencies, including NASA, the Department of Justice, and the Social Security Administration, and found troubling vendor practices: 1️⃣ Double charging – Agencies must repurchase licenses to use software in the cloud. 2️⃣ Migration fees – Vendors charge extra to move on-prem software to cloud. 3️⃣ Lock-in tactics – Some software only runs on a specific cloud provider. 4️⃣ Data ransom – Agencies must pay to regain ownership of their data after migration. Agencies are facing hidden fees and vendor-imposed restrictions that are doing the opposite. Instead of cutting costs, cloud migration is becoming a financial headache. Instead of flexibility, agencies are stuck with vendor-controlled limitations. Instead of seamless modernization, they’re paying for workarounds. I’ve seen companies struggle with: • Unexpected migration costs when switching cloud providers. • Vendor lock-in that makes integration nearly impossible. • Rigid licensing terms that prevent growth and scalability. So how do you avoid these costly mistakes? → Negotiate smarter contracts to ensure flexibility across providers. → Use enterprise-wide agreements to avoid reliance on a single vendor. → Implement Software License Management (SLM) to track and optimize costs. → Strengthen procurement strategies to spot hidden restrictions before signing. → Prioritize open standards to keep systems interoperable. Repost ♻️ to share with your network. P.S. Have you ever faced hidden fees in a cloud contract?

Python just broke JavaScript’s 10-year streak. For the first time in a decade,  Python is the most-used language on GitHub. This shift comes as Python has become the go-to language for AI, machine learning, and data science. ✅ Python overtook JavaScript, driven by AI, machine learning, and data science. ✅ TypeScript surpassed Java, proving Devs want more structure and scalability. ✅ Jupyter Notebook usage jumped 92%, showing Python’s dominance in AI workflows. But it's not just about the language, AI is transforming the way developers work. → AI-generated code contributions surged 98%. → Developers using AI fixed bugs 3x faster. → More projects rely on AI-assisted code than ever before. The language’s simplicity, flexibility, and power in AI make it indispensable for the future of development. It’s the foundation of key machine learning and data science libraries like TensorFlow, PyTorch, and Pandas. Right now, AI is driving innovation, and it’s clear Python is benefiting. But what happens when AI evolves further and shifts its preferences? • As AI tools advance, will language preferences shift again? • How much control will developers have if AI guides development? We are witnessing a shift from developers writing code to AI making key decisions about how code is generated and optimized. P.S. Have you noticed AI changing how you code? P.P.S.: Image Credit @Gina Acosta Gutiérrez #Python #AIinDevelopment #MachineLearning #AIRevolution #PythonCommunity #DataScience #CodingWithAI #TechTrends2025 #GitHubTrends #AIInnovation #PythonForAI #FutureOfCoding #AIandDevelopers #TechShift #PythonDominance #OpenSourceCommunity #AutomationInTech #AIProductivity #TechEcosystem #AIProgramming #PythonLove #ArtificialIntelligence #AI

Your devices just got hacked. No weird links. No shady apps. One second you are sipping coffee. The next, an attacker thousands of miles away has full control of your messages, photos and microphone. And you did not even touch your phone. That is how zero-click exploits work. This is a type of cyberattack that allows malicious actors to compromise a device without any interaction from the user. That is how the FORCEDENTRY exploit worked. Developed by the NSO Group, it silently installed Pegasus spyware on iPhones, targeting journalists, activists and even world leaders. But Apple did not take it lightly. → They added Lockdown Mode to protect people in danger, like activists.  Go to Settings > Privacy & Security > Lockdown Mode and toggle it on. → They offered $1.5 million as a security bounty program to anyone who finds these tricks. → They hunted bugs with groups like Citizen Lab and built BlastDoor to block attacks. Even if you’re not a high-profile target you are not invisible. Because hackers go after vulnerabilities. Turn off features that are not in use, such as: AirDrop: Set it to "Contacts Only" or disable it entirely (Settings > General > AirDrop) • Use a Secure DNS Use a secure DNS service like Cloudflare's 1.1.1.1 or Google Public DNS to block malicious domains that might be used in zero-click exploits. Zero-click exploits don’t need your permission. So don’t give them a chance. Stay updated. Lock down your device. Be proactive. ♻️ Repost to help others stay secure. P.S.: Are you using secure DNS services like Cloudflare or Google DNS.

Who is a woman who has inspired your career? #IWD25

Which cloud provider should be used when building a big data solution? Choosing the wrong one can be costly. Each cloud provider offers similar core services: 1️⃣ Data ingestion – Structured and unstructured data intake. 2️⃣ Raw data storage – Secure, scalable, and compliant repositories. 3️⃣ Data processing – Filtering, transformation, and real-time analytics. 4️⃣ Data warehousing – Key-value, relational, and OLAP databases. 5️⃣ Visualization & insights – Dashboards, ML models, and predictive analytics. At first glance, they seem identical. Even their services have different names but do the same thing. For example, AWS Lambda = Azure Function = Google Cloud Functions. So, what really sets them apart? • AWS dominates with global scalability and enterprise-grade reliability. • Azure excels in Microsoft integration and hybrid cloud environments. • Google Cloud leads in AI-driven analytics and cost-effective big data processing. The worst way to choose is based on popularity. Too many companies pick based on popularity instead of strategy. Too many businesses regret rushing their decision. Too many leaders assume all clouds are interchangeable. The best way to choose is to align with your business needs, even if that means going multi-cloud. I've helped companies untangle cloud choices, and one thing is clear: The biggest provider isn’t always the best fit. PS: Have you ever regretted your cloud choice? PPS: Image Credit: Satish Chandra Gupta.

"Wait… I never authorized that transaction!" That’s the last thing you want to see in your inbox. By the time you notice, it’s too late. I’ve seen how small security gaps lead to big losses. Hackers don’t need advanced tools, Just one weak spot in your defenses. 1️⃣ Use a Password Manager A password manager locks it tight with unique, complex passwords for every account. 2️⃣ Install Antivirus Software  A strong antivirus detects and removes them before they do damage. 3️⃣ Enable Multi-Factor Authentication (MFA)   A stolen password isn’t enough if MFA is on.  This simple step blocks unauthorized logins before they happen. 4️⃣ Be Cautious Online  One wrong click can compromise everything.  Avoid suspicious links, fake emails, and unsecured websites. 5️⃣ Secure Your Devices  Hackers don’t just attack online.  Use RFID-blocking wallets for credit cards and encrypt your data to keep it safe. You don’t need to be a cybersecurity expert to stay protected. By making security a habit, you can protect your business, your data, and your future. P.S. Have you ever fallen for a phishing email?

We might not have enough power to keep AI running. AI is growing faster than our infrastructure can handle. → AI workloads are growing fast. More processing means more heat. → Cooling already takes up 40% of a data center’s energy. → By 2030, power demand will surge by 160%. But a new breakthrough from @UT Austin will have huge impact on the AI energy needs. A research team at UT Austin has developed a new cooling material that’s 72% more efficient than current commercial technologies. • It removes 2,760 watts of heat from just 16 cm². • It cuts cooling pump energy use by 65%. When implemented across the industry, this innovation could reduce total data center energy usage by 5%. It improves both environmental impact and operational costs. This innovation could enable the development of more compact, energy-efficient facilities. Because if we don’t fix this now, AI’s biggest limitation won’t be compute power. It’ll be sustainability. P.S. Do you think AI’s energy demands will impact startups?

Cloud complexity is the tax you pay for poor planning. Less than 1 in 5 IT pros say their cloud setup actually meets business needs. The promise of scalability and efficiency often turns into over-complexity and unexpected costs. → 23% admit hybrid cloud made IT harder to manage. → 16% have already moved workloads back on-prem. → 12% suffer long-term financial damage from poor migration. Because most businesses fall into the same traps. I’ve seen businesses waste thousands on cloud setups that only added complexity. I’ve watched teams spend weeks fixing issues instead of focusing on growth. It doesn’t have to be this way. • Keep it simple. More tools ≠ better results. • Automate smartly. Repetitive work kills progress. • Plan ahead. Avoid migrations that cost more than they save. • Use AI wisely. Predict and prevent problems, don’t just react. This is exactly why I built ComputeSphere to help businesses scale without stress. Because cloud should work for you, not against you. PS: What’s the most frustrating part of your cloud setup right now? P.P.S. Image Credit: © D. Fletcher for CloudTweaks.com . . . AI-driven growth, automation for businesses, cloud solutions for small businesses, enterprise-grade solutions for small businesses, scalable business systems, operational efficiency, business automation, AI integrations, simplifying workflows, cost-saving automation, flexible business solutions, tech for entrepreneurs, sustainable business growth, smart scaling, cloud strategy, workflow optimization, business transformation with AI, enterprise AI solutions, data-driven business decisions, future-proofing businesses, business growth without complexity, cloud-based solutions for entrepreneurs, productivity tools for small businesses, efficient cloud hosting, seamless business scaling, cost-effective AI, business process optimization, simplified system migrations, easy business automation, AI-first business strategies.

Cybersecurity Leaders Are Burned Out! Gartner Peer Community surveyed 178 cybersecurity leaders to uncover the most common causes. Among these leaders: ➝ 62% personally experienced burnout at least once ➝ with 44% reporting multiple instances. The two reasons uncovered were: 1.Excessive Responsibilities  2. Long Hours "37% of cybersecurity leaders say unrealistic expectations of the security function and/or for someone in their role have significantly contributed to their burnout." I've gone through burnout myself, multiple times. Start with these simple steps: 1) Track Your Sleep 2) Define Your Priorities 3) Set Healthy Boundaries 4) Micro-Dose Your Recovery 5) Build Stronger Relationships Repost to share with your network.

Nvidia’s revenue is up 94%, but there’s a massive problem brewing behind the scenes. What really caught my attention was the challenge they are facing. As AI demand is rising booming, Nvidia’s biggest challenge isn’t competition—it’s keeping pace with production. As someone who is passionate about AI and its potential to transform industries, I'm excited to see how Nvidia tackles their supply chain issues. Their GPUs are in high demand from the big players - AWS, Microsoft, and Google Cloud. But Nvidia's supply chains are struggling to keep up. They cannot produce enough GPUs to meet the overwhelming need. Nvidia President and CEO Jensen Huang said during the call: “It is the case that demand exceeds our supply, and that’s expected as we’re in the beginnings of this generative AI revolution.” It is a scaling challenge. Nvidia’s challenge is a preview of what is coming for any organization riding this wave. I'm curious to see how NVIDIA will navigate this challenge. Can they keep up with the AI revolution's breakneck pace? Only time will tell, but one thing is for sure - the future of AI is exciting, and Nvidia's at the forefront of it! Repost ♻️ if you’re excited about AI’s potential. P.S. Do you think AI demand will outpace hardware production for other industries too?