2026-02-28 15:11:23
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## The End of CI/CD Pipelines: The Dawn of Agentic DevOps 
By @davidiyanu [ 10 Min read ]
GitHub's agent fixed my flaky test in 11 minutes. No human wrote code. But when it fails, instead of a stack trace, you get an outcome. Read More.
By @davidiyanu [ 5 Min read ] RAG fails less from the LLM and more from retrieval: bad chunking, weak metadata, embedding drift, and stale indexes. Fix the pipeline first. Read More.
By @stevebeyatte [ 7 Min read ] Compare the 7 best co-parenting apps in 2026, including BestInterest, OurFamilyWizard, and TalkingParents. Find the right app for high-conflict situations. Read More.
By @playerzero [ 15 Min read ] Modern software teams ship faster than ever, but defect resolution lags; PlayerZero aligns people, process, and context for predictable reliability. Read More.
By @ipinfo [ 8 Min read ] Analysis of 170M residential proxy IPs reveals rapid rotation and 46% cross-provider overlap—breaking traditional fraud detection models. Read More.
By @thomascherickal [ 14 Min read ] OpenClaw lets you run frontier AI models like Minimax M2.5 and GLM-5 100% locally on Mac M3 or DGX Spark — zero API costs, total privacy. Here's how. Read More.
By @aimodels44 [ 8 Min read ] A new study suggests AGENTS.md-style repo context files can reduce coding-agent success while raising inference cost. Here’s why—and what to do instead. Read More.
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By @dataops [ 3 Min read ] Technical debt isn’t refactoring—it’s hidden risk. A powerful racecar analogy to help engineers explain why cutting corners can end in disaster. Read More.
By @birukum [ 11 Min read ] Agentic AI workflows can create a financial black hole. Learn how semantic caching uses vector similarity to cut your LLM token burn by 24%. Read More.
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By @omotayojude [ 3 Min read ] When an AI agent's PR was rejected by Matplotlib, it didn't just close the tab it wrote an angry hit piece on the maintainer. Is this the future of open source? Read More.
By @hackernoon-courses [ 4 Min read ] Learn how to write content that stands out in the age of AI, crafting a voice and style no model or copycat can replicate. Read More.
By @ArunDHANARAJ_gfaknebg [ 14 Min read ] Compare Claude Opus 4.6 and GPT‑5.3 Codex across reasoning, coding, benchmarks, pricing, and safety to guide enterprise AI and agentic workload decisions.
By @nickzt [ 5 Min read ] Scaling AI for the real world requires peeling back the layers of abstraction we've gotten too comfortable with. Read More.
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MEXC reports 2.35M users across its AI trading suite, with 10.8M interactions and record activity during October’s flash crash. Read More.
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2026-02-28 11:28:34
Batman made his first appearance in 1939. When you have a character who has been around for 80 years, they’re bound to change their appearance from time to time. So, it only makes sense for video games like Batman: Arkham Knight to take advantage of this and add different alternative costumes that players can pick and choose from. Some of these were hits, some of these were misses, and some were just okay. Let’s take a look at the 5 biggest hits (at least, in my opinion). Here are the 5 best batsuits from Batman: Arkham Knight.
One of my favorites is the default one, the v8.03. We get this one early into the game, when Batman realizes he needs a little something extra, and his old costume just won’t do. It looks sleek, heavy, and the black looks amazing. This is definitely the best-looking default batsuit in the entire series.
\ There are 2 other versions of this suit: the 8.04 and 8.05. The 8.04 stays perfectly pristine, so it doesn’t get any battle damage as the 8.03 does. Then there’s the 8.05. This one is similar, with the exception of the golden bat symbol on the chest.
\ I’m not a fan of the golden bat symbol, and I actually like that the 8.03 can get damaged and cut up. It shows the toll that the night has taken on Batman.
Some people like it when the batsuit is gray; others prefer it when it’s black. I like this one because it falls right in the middle. It looks like a dark gray, but from a different perspective, you can technically say that it’s a light black. What really makes the Batman Inc. suit one of my favorites, though, is the bat symbol on his chest. The yellow oval behind the black bat symbol makes it really striking, and it’s one of the first things your eyes notice.
\ There are similar batsuits like the one from the 1989 movie that have a similar look. However, the Batman Inc. one has a better bat symbol and cowl. That’s why I put it above the 1989 one and above most other ones.
\ The Batman Flashpoint suit is damn near perfect. The red accents all throughout it, such as in his pouches, eyes, and bat symbol, really make the whole thing stand out. Plus, having the body be gray with the cowl, gauntlets, and boots be completely black was such a great idea. The cherry on top, the thing that makes this costume stunning, is the double-handguns, one on each side. Like I said, damn near perfection.
\ So, what don’t I like about it? My least favorite thing about it is the strange shoulder guards. Maybe if they were smaller and less pointy, I would be into it. Even better would be if they were completely gone. With all that said, though, this is still one of the best skins in the game.
I said I like the Batman Inc. suit because it’s the perfect mix between black and gray. I like the Batman v Superman one for a completely different reason. This one is very clearly gray; there’s no mistaking it. There are others that are gray, like the First Appearance one, but there is something different about this particular one. It’s the fabric. I’m not sure how to describe it, but the fabric of the suit is unlike any other.
\ It sort of looks like a type of Kevlar, which is completely different from the tights that some of the other costumes appear to be made out of. That, combined with the gigantic bat symbol, makes it look phenomenal. I’m a sucker for a good bat symbol, what can I say?
This might be a hot take, but my all-time favorite batsuit in the Arkham Knight game is the Batman Beyond one. Don’t get me wrong, I love the others on this list, but this one is just on a completely different level. I really like the red accents and how mechanized the whole suit looks. It has a whole cyborg thing going on that I personally enjoy. There are some caveats to it, though, that I will admit to.
\ The mouthpiece is a bit strange-looking. You have this whole futuristic costume, and it looks like the mouthpiece is just made out of cloth or something. Not a fan. The second biggest critique is that it looks nothing like the Batman Beyond suit from the animated show.
\ I can understand and accept these two flaws, but that doesn’t bring down my enjoyment of the costume. In my opinion, the Batman Beyond suit is the best-looking one in Batman: Arkham Knight. You know what, I might have to replay the whole game again just to look at these cool skins.
\ Feature image source
2026-02-28 09:18:17
If you hang around startup circles in the Bay Area long enough, you’ll start hearing something unexpected between funding rounds and AI debates: founders quietly Googling “car rental in UAE” and checking flight prices to Dubai and Abu Dhabi. What started as curiosity has turned into a real trend. From San Francisco to the sands of the Arabian Peninsula, American tech talent is seriously eyeing the United Arab Emirates—and not just for a quick conference or a flashy vacation.
So what’s driving the shift?
Let’s call it what it is. The Bay Area is still iconic, but it’s also expensive, hyper-competitive, and increasingly saturated. Sky-high rents, intense regulation, talent wars, and a constant hustle culture can wear even the most ambitious founder down. After years of grinding in co-working spaces and chasing Series A funding, some U.S. entrepreneurs are looking for a reset.
The UAE, especially Dubai and Abu Dhabi, is pitching itself as that reset button. Lower personal income taxes, streamlined business setup processes, and aggressive government support for innovation make the region hard to ignore. For founders used to navigating layers of red tape back home, the efficiency can feel almost unreal.
One of the biggest surprises for Americans exploring the UAE tech scene is how hands-on—and forward-thinking—the government is. Artificial intelligence, fintech, climate tech, space technology: these aren’t just buzzwords on a conference banner. They’re central to national strategy.
Free zones tailored to tech companies offer 100% foreign ownership and simplified licensing. Major funds and sovereign wealth investors actively back innovation. In many cases, founders aren’t just tolerated—they’re welcomed with open arms and real incentives.
Compare that to the sometimes fragmented regulatory environment in the U.S., and it’s easy to see why some builders are thinking, “Why not give this a shot?”
There’s still a persistent stereotype in the U.S. that the Gulf economy runs purely on oil. That narrative is outdated. The UAE has spent decades diversifying its economy, investing heavily in infrastructure, tourism, logistics, and now digital transformation.
Walk through Dubai Internet City or Hub71 in Abu Dhabi and you’ll see a mix of global companies, scrappy startups, and venture-backed disruptors. English is widely spoken. Contracts are often structured in ways that feel familiar to U.S. founders. The vibe? Surprisingly international and business-friendly.
For tech professionals who’ve spent their careers building products for global markets, the UAE’s geographic position—bridging Europe, Asia, and Africa—is a strategic advantage. A product launched in Dubai can scale across multiple regions without being locked into one market.
Let’s talk lifestyle, because it matters. The UAE isn’t just pitching spreadsheets and tax breaks. It’s selling quality of life. Modern apartments, world-class restaurants, beach access, and relatively high levels of safety are all part of the package.
Yes, the summer heat is intense. But the infrastructure is built for it. Offices, malls, and residential buildings are climate-controlled. Everything runs efficiently. For many Americans, the biggest adjustment isn’t the temperature—it’s the pace. Things move fast. Deals close quickly. Bureaucracy, when it exists, is often surprisingly streamlined.
And when it comes to getting around, practicality kicks in. Cities like Dubai are spread out, with business districts, residential communities, and innovation hubs connected by wide highways. While public transportation exists, most professionals find that having a car makes daily life significantly easier. Whether you’re commuting to a co-working space, heading to investor meetings, or exploring new neighborhoods, renting a car is often the smartest move—especially during your first few months while you figure out where to settle.
The pandemic permanently shifted how tech workers think about location. If you can code from anywhere, why limit yourself to one zip code? The UAE capitalized on this shift by introducing long-term visas and remote work permits designed specifically for global talent.
Suddenly, relocating doesn’t mean cutting ties with U.S. clients or investors. Many founders maintain American entities while building regional operations in the UAE. It’s less about abandoning Silicon Valley and more about expanding beyond it.
This hybrid model is attractive. Keep your Delaware C-corp, but base your operations in a city that offers global connectivity, strong infrastructure, and competitive costs. For a generation raised on flexibility and scale, it’s a compelling pitch.
Of course, moving halfway across the world isn’t a casual decision. Cultural differences, legal frameworks, and market dynamics require research and adaptability. Not every startup will thrive in the Gulf, and not every founder will feel at home.
But the reputation factor is shifting. What once seemed like a bold or risky move now feels strategic. U.S. tech talent isn’t just chasing sunshine and skyscrapers. They’re chasing opportunity—new markets, new investors, and a chance to build in an ecosystem that’s actively evolving.
From San Francisco to the sands, the flow of ideas—and people—is becoming more global. The UAE isn’t replacing Silicon Valley, but it’s carving out its own lane as a serious contender in the tech world. For American founders and engineers tired of the grind or hungry for international expansion, it’s a place worth exploring.
Pack your laptop. Line up your meetings. Maybe start with a short-term stay and a rental car to navigate the city like a local. You might just discover that the future of your startup isn’t limited to the Bay Area. Sometimes, the next big move starts with a one-way ticket and a willingness to see what’s possible beyond the familiar skyline.
:::info This article is published under HackerNoon's Business Blogging program.
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2026-02-28 08:47:12
This guide compares the 7 leading requirements management software solutions in 2026, from modern platforms like Jama Connect to legacy tools like IBM DOORS and lightweight options like Excel. The best choice depends on your product complexity, regulatory requirements, and team structure—but most organizations opt for modern tools like Jama Connect.
2026-02-28 08:35:16
Analysis
Experiments Results
Practical Inference Speedup Evaluation
A. Appendix / supplemental material
We measure our sparsified models’ performance on tasks included in OpenLLM Leaderboard which include 25-shot Arc-Challenge [13], 10-shot Hellaswag [65], 5-shot MMLU [22], 0-shot TruthfulQA [35], 5-shot Winogrande [51] and 8-shot GSM8K [14]. In addition, we also follow Llama 2’s evaluation task included commonsense reasoning tasks. We report the average of PIQA [8], SCIQ [26], ARC easy [13], OpenBookQA [41]. We compare our models to several external open-source LLMs, including Gemma-2B [58], Mistral-7B [24] and Mixtral-47B [25].
\
\
\ \ Table 6 shows the results from different models. TurboSparse-Mistral-7B outperforms Gemma-2B by far, while only activating 3B parameters. TurboSparse-Mixtral-47B outperforms the original Mixtral-47B with only 4.5B parameters activated. The results demonstrate that LLMs with ReLU based intrinsic activation sparsity can keep the same or better performance while hold the significant FLOPs reduction.
\
:::info Authors:
(1) Yixin Song, Institute of Parallel and Distributed Systems (IPADS), Shanghai Jiao Tong University;
(2) Haotong Xie, Institute of Parallel and Distributed Systems (IPADS), Shanghai Jiao Tong University;
(3) Zhengyan Zhang, Department of Computer Science and Technology, Tsinghua University;
(4) Bo Wen, Institute of Parallel and Distributed Systems (IPADS), Shanghai Jiao Tong University;
(5) Li Ma, Shanghai Artificial Intelligence Laboratory;
(6) Zeyu Mi, Institute of Parallel and Distributed Systems (IPADS), Shanghai Jiao Tong University Mi [email protected]);
(7) Haibo Chen, Institute of Parallel and Distributed Systems (IPADS), Shanghai Jiao Tong University.
:::
:::info This paper is available on arxiv under CC BY 4.0 license.
:::
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2026-02-28 08:31:06
Analysis
Experiments Results
Practical Inference Speedup Evaluation
A. Appendix / supplemental material
In the previous section, we have demonstrated that dReLU can be a better choice for ReLUfication. The main question now is whether dReLU based ReLUfication can recover the original model’s performance while achieving higher sparsity. The following sections will discuss the experiments that aimed at answering this question.
\ Experimental setup. We consider two representative models: Mistral-7B and Mixtral-47B. We substitute the original SwiGLU based FFN with dReLU based FFN and then continue pretraining.
\ Pretraining datasets. Due to the ReLUfication process, the restoration of model capability is closely related to the corpus used for recovery training. We collected as much corpus as possible from the open-source community for training, such as Wanjuan-CC [48], open-web-math [46], peS2o [54], Pile [19], The Stack [28], GitHub Code [1] and so on. The detailed mixture ratio is as shown in the following table 4:
\
\
\ \ SFT datasets. After pretraining, we utilize the high-quality SFT datasets to further improve our model’s performance, including orca-math-word-problems [43], bagel [27].
\ Hyper-parameters. The hyperparameters for our ReLUfication are based on empirical results from previous works [69]. We utilize the llm-foundry framework for training [44] and employ FSDP parallelism.
\ Our models are trained using the AdamW optimizer [38] with the following hyper-parameters: β1 = 0.9 and β2 = 0.95. We adopt a cosine learning rate schedule and use the default values for weight decay and gradient clipping (see Table 5 for more details). In total, we pretrain our models on 150B tokens.
\
\
\
:::info Authors:
(1) Yixin Song, Institute of Parallel and Distributed Systems (IPADS), Shanghai Jiao Tong University;
(2) Haotong Xie, Institute of Parallel and Distributed Systems (IPADS), Shanghai Jiao Tong University;
(3) Zhengyan Zhang, Department of Computer Science and Technology, Tsinghua University;
(4) Bo Wen, Institute of Parallel and Distributed Systems (IPADS), Shanghai Jiao Tong University;
(5) Li Ma, Shanghai Artificial Intelligence Laboratory;
(6) Zeyu Mi, Institute of Parallel and Distributed Systems (IPADS), Shanghai Jiao Tong University Mi [email protected]);
(7) Haibo Chen, Institute of Parallel and Distributed Systems (IPADS), Shanghai Jiao Tong University.
:::
:::info This paper is available on arxiv under CC BY 4.0 license.
:::
\
