Seekr Technologies, the trusted AI company, today announced the appointment of Lloyd Cope as Chief Revenue Officer (CRO). Cope brings over two decades of sales and leadership experience across mission-critical enterprise and defense environments and will lead Seekr in its next phase of strategic growth and global go-to-market execution. He...
The post <a href="https://ai-techpark.com/seekr-appoints-ex-palantir-exec-lloyd-cope-as-cro/">Seekr Appoints Ex-Palantir Exec Lloyd Cope as CRO</a> first appeared on <a href="https://ai-techpark.com">AI-Tech Park</a>.

قامت شركة Seekr Technologies بخطوة مهمة من خلال تعيين لويد كوبر كمدير جديد للإيرادات. مع أكثر من 20 عامًا من الخبرة في المبيعات والقيادة، خاصة في قطاعات المؤسسات والدفاع، من المتوقع أن يقود كوبر النمو الاستراتيجي لشركة Seekr ويعزز وجودها في السوق العالمية. هذه التعيينات مهمة حيث تسعى Seekr لتعزيز موقعها في صناعة الذكاء الاصطناعي، مما يجعل هذا الوقت مثيرًا للشركة وأصحاب المصلحة.

Seekr Technologies ha dado un paso significativo al nombrar a Lloyd Cope como su nuevo Director de Ingresos. Con más de 20 años de experiencia en ventas y liderazgo, especialmente en los sectores empresarial y de defensa, se espera que Cope impulse el crecimiento estratégico de Seekr y mejore su presencia en el mercado global. Este nombramiento es crucial ya que Seekr busca fortalecer su posición en la industria de la IA, lo que convierte este momento en algo emocionante para la empresa y sus partes interesadas.

Seekr Technologies a fait un mouvement significatif en nommant Lloyd Cope comme nouveau directeur des revenus. Fort de plus de 20 ans d'expérience dans la vente et le leadership, notamment dans les secteurs de l'entreprise et de la défense, Cope devrait propulser la croissance stratégique de Seekr et renforcer sa présence sur le marché mondial. Cette nomination est cruciale alors que Seekr vise à consolider sa position dans l'industrie de l'IA, rendant ce moment passionnant pour l'entreprise et ses parties prenantes.

Seekr Technologies has made a significant move by appointing Lloyd Cope as its new Chief Revenue Officer. With over 20 years of experience in sales and leadership, particularly in enterprise and defense sectors, Cope is expected to drive Seekr's strategic growth and enhance its global market presence. This appointment is crucial as Seekr aims to strengthen its position in the AI industry, making it an exciting time for the company and its stakeholders.

Seekr Appoints Ex-Palantir Exec Lloyd Cope as CRO

&nbsp;As US educators embrace AI in the classroom, firms are selling software to flag mentions of self-harm, raising concerns over privacy and control.

مع تزايد استخدام تقنية الذكاء الاصطناعي في الفصول الدراسية في الولايات المتحدة، بدأ المعلمون في استخدام الدردشة الآلية لمراقبة رفاهية الطلاب. بينما يمكن أن تساعد هذه الأدوات في تحديد علامات السلوكيات الذاتية الضارة، فإنها تثير أيضًا مخاوف كبيرة بشأن الخصوصية ومدى المراقبة في البيئات التعليمية. قد يؤثر هذا التحول نحو المراقبة المستمرة على ثقة الطلاب وحريتهم، مما يجعله قضية حاسمة للآباء والمعلمين على حد سواء.

A medida que la tecnología de IA se vuelve más común en las aulas de EE. UU., los educadores están utilizando cada vez más chatbots para monitorear el bienestar de los estudiantes. Si bien estas herramientas pueden ayudar a identificar signos de autolesionismo, también plantean preocupaciones significativas sobre la privacidad y el alcance de la vigilancia en los entornos educativos. Este cambio hacia la vigilancia constante podría afectar la confianza y la libertad de los estudiantes, convirtiéndolo en un tema crítico para padres y educadores.

Alors que la technologie de l'IA devient de plus en plus courante dans les salles de classe aux États-Unis, les éducateurs utilisent de plus en plus des chatbots pour surveiller le bien-être des élèves. Bien que ces outils puissent aider à identifier des signes de comportements autodestructeurs, ils soulèvent également d'importantes préoccupations concernant la vie privée et l'étendue de la surveillance dans les établissements éducatifs. Ce passage vers une surveillance constante pourrait affecter la confiance et la liberté des élèves, ce qui en fait un enjeu crucial pour les parents et les éducateurs.

As AI technology becomes more prevalent in classrooms across the US, educators are increasingly using chatbots to monitor student well-being. While these tools can help identify signs of self-harm, they also raise significant concerns about privacy and the extent of surveillance in educational settings. This shift towards constant monitoring could impact students' trust and freedom, making it a critical issue for parents and educators alike.

Chatbots Are Sparking a New Era of Student Surveillance

The TRADE sits down with Nicholas Phillips, market structure research analyst at Bloomberg Intelligence (BI), following the publication of BI's 'European institutional equity trading study 2025’ report, to explore Europe’s renewed trading momentum, what to look out for in 2026, and the continued developments in post-trade, dark trading caps, rising bilateral, and more.
The post <a href="https://www.thetradenews.com/fireside-friday-with-bloomberg-intelligences-nicholas-phillips/">Fireside Friday with… Bloomberg Intelligence’s Nicholas Phillips</a> appeared first on <a href="https://www.thetradenews.com">The TRADE</a>.

في مناقشة حديثة، شارك نيكولاس فيليبس من بلومبرغ إنتليجنس رؤى حول نتائج تقريرهم 'دراسة تداول الأسهم المؤسسية الأوروبية 2025'. وأبرز انتعاش نشاط التداول في أوروبا وما يمكن توقعه في عام 2026، بما في ذلك التقدم في عمليات ما بعد التداول وتنظيمات التداول المظلم. هذه المحادثة مهمة لأنها تسلط الضوء على المشهد المتطور لتداول الأسهم، وهو أمر حاسم للمستثمرين والمشاركين في السوق الذين يسعون للتنقل في تعقيدات السوق الأوروبية.

En una reciente discusión, Nicholas Phillips de Bloomberg Intelligence compartió información sobre los hallazgos de su informe 'European institutional equity trading study 2025'. Destacó el resurgimiento de la actividad de trading en Europa y las tendencias que se anticipan para 2026, incluyendo avances en los procesos post-negociación y regulaciones sobre trading oscuro. Esta conversación es significativa ya que arroja luz sobre el paisaje en evolución del trading de acciones, lo cual es crucial para los inversores y participantes del mercado que buscan navegar por las complejidades del mercado europeo.

Lors d'une récente discussion, Nicholas Phillips de Bloomberg Intelligence a partagé des informations sur les résultats de leur rapport 'European institutional equity trading study 2025'. Il a souligné la résurgence de l'activité de trading en Europe et les tendances à anticiper en 2026, y compris les avancées dans les processus post-négociation et les réglementations sur le trading obscur. Cette conversation est importante car elle éclaire l'évolution du paysage du trading d'actions, ce qui est crucial pour les investisseurs et les acteurs du marché cherchant à naviguer dans les complexités du marché européen.

In a recent discussion, Nicholas Phillips from Bloomberg Intelligence shared insights on the findings of their 'European institutional equity trading study 2025' report. He highlighted the resurgence of trading activity in Europe and what trends to anticipate in 2026, including advancements in post-trade processes and dark trading regulations. This conversation is significant as it sheds light on the evolving landscape of equity trading, which is crucial for investors and market participants looking to navigate the complexities of the European market.

Fireside Friday with… Bloomberg Intelligence’s Nicholas Phillips

Hi there. In this article, I'll be going over the process of how you can create a macOS 26 Tahoe USB bootable installation drive.

<h2>
 
 
 YouTube Video
</h2>

If you would prefer to see a video of this article, there is a video version available on YouTube below:

<iframe width="710" height="399" src="https://www.youtube.com/embed/BBiWy6FrtM4">
</iframe>


<h2>
 
 
 Requirements
</h2>

To do this, you'll need macOS 10.15 or above (I used macOS 15) and a 32GB USB stick or higher to create the installation drive.

Before you start, make sure to backup any data that is on the USB stick as the USB stick will be erased as part of the process.

<h2>
 
 
 Downloading the macOS 26 Tahoe Installer
</h2>

Unlike previous versions of macOS, macOS 26 Tahoe is not available in the App store. It can only be downloaded via the command line for the full version that is used to create an installation disk.

To begin with, you'll need to open the terminal application. To this, use spotlight by pressing command and space together. Then, type terminal and hover over to the terminal application. It looks like a black box with a white arrow. Left click on it to open the application.

Your terminal may look different to mine but don't worry.

You can also get to it by opening a Finder window, going to Applications, then Utilities and then double clicking on Terminal.

First, you need to determine what the latest version of Tahoe is. There are two ways to do this. First, you can use this <a href="">webpage</a>, which shows it is being 26.1 at the time of writing this article.

<a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2F7p6roxf0ufy5frukae2c.png" class="article-body-image-wrapper"><img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2F7p6roxf0ufy5frukae2c.png" alt="Image 1" width="800" height="354"></a>

The second method is to run the following command in the terminal: 


<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>softwareupdate --list-full-installers
</code></pre>

</div>



The latest version is at the top, which again is 26.1.

<a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Fcogm6l42kciu08k750nl.png" class="article-body-image-wrapper"><img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Fcogm6l42kciu08k750nl.png" alt="Image 2" width="800" height="461"></a>

The next step is to download the installer for macOS 26.1. To do that, run the following command. If a newer version is available, replace <code>26.1</code> with that version, if you want to: 


<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>softwareupdate --fetch-full-installer --full-installer-version 26.1
</code></pre>

</div>



It will now download the installer. This will take some time.

<a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Ffqmovocs202pw2bwdjib.png" class="article-body-image-wrapper"><img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Ffqmovocs202pw2bwdjib.png" alt="Image 3" width="800" height="462"></a>

<h2>
 
 
 Creating the USB Installation Drive
</h2>

Now that the installer has finished downloading, you should be able to see it in the Applications folder in Finder.

<a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2F9gkffyhw77ufowhtpd54.png" class="article-body-image-wrapper"><img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2F9gkffyhw77ufowhtpd54.png" alt="Image 4" width="800" height="495"></a>

The next step is to make the USB installation drive. First, make sure your USB stick is connected to your Mac.

Mine is connected and it's called usbstick.

I would recommend renaming your USB stick to a name that has no spaces to make it easier.

Once again, remember to backup anything that is on the USB stick that you want to keep.

When you are ready, run the following command in the terminal. Replace <code>usbstick</code> with the name of your USB stick. 


<div class="highlight js-code-highlight">
<pre class="highlight shell"><code>sudo /Applications/Install\ macOS\ Tahoe.app/Contents/Resources/createinstallmedia --volume /Volumes/usbstick
</code></pre>

</div>



Press enter and then type in your password, or the username and password for an administrator account if your account doesn't have that level of permission.

When it asks you to confirm the USB stick can be erased, press <code>y</code> and then enter.

Your USB stick will disappear from Finder and then come back with the name of Install macOS Tahoe. This is normal.

The progress will be shown on the screen.

Once it has completed, the terminal will look like the below image.

<a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Ff69snvwmd4xsra2ugsos.png" class="article-body-image-wrapper"><img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Ff69snvwmd4xsra2ugsos.png" alt="Image 5" width="800" height="462"></a>

You can now use that to boot from and install, or reinstall macOS 26 Tahoe on a <a href="">supported Mac</a>.

Thanks for reading and have a nice day!

يوفر هذا المقال دليلًا بسيطًا حول كيفية إنشاء محرك USB قابل للتشغيل لتثبيت macOS 26 Tahoe، مما يسهل على المستخدمين تثبيت أو ترقية نظام التشغيل. مع تعليمات واضحة وتوافر فيديو تعليمي على يوتيوب، يلبي احتياجات المتعلمين البصريين وأولئك الذين يفضلون الإرشادات المكتوبة. هذا مهم بشكل خاص لأن وجود محرك قابل للتشغيل يمكن أن يبسط عملية استكشاف الأخطاء وإصلاحها واستعادة النظام، مما يضمن أن المستخدمين يمكنهم الحفاظ على أجهزتهم بفعالية.

Este artículo ofrece una guía sencilla sobre cómo crear una unidad USB de instalación de macOS 26 Tahoe, facilitando la instalación o actualización del sistema operativo. Con instrucciones claras y un tutorial en video disponible en YouTube, se adapta tanto a los aprendices visuales como a aquellos que prefieren la orientación escrita. Esto es especialmente importante, ya que tener una unidad de arranque puede simplificar la solución de problemas y la recuperación del sistema, asegurando que los usuarios puedan mantener sus dispositivos de manera efectiva.

Cet article propose un guide simple pour créer un lecteur USB d'installation bootable macOS 26 Tahoe, facilitant ainsi l'installation ou la mise à niveau du système d'exploitation. Avec des instructions claires et un tutoriel vidéo disponible sur YouTube, il s'adresse à la fois aux apprenants visuels et à ceux qui préfèrent les conseils écrits. Cela est particulièrement important car avoir un lecteur bootable peut simplifier le dépannage et la récupération du système, garantissant que les utilisateurs peuvent maintenir efficacement leurs appareils.

This article provides a straightforward guide on creating a macOS 26 Tahoe USB bootable installation drive, making it easier for users to install or upgrade their operating system. With clear instructions and a video tutorial available on YouTube, it caters to both visual learners and those who prefer written guidance. This is particularly important as having a bootable drive can simplify troubleshooting and system recovery, ensuring that users can maintain their devices effectively.

How To Create A macOS 26 Tahoe USB Installation Drive

You don’t need to shout to be heard; you need to be clear and verifiable. Teams that treat publishing like a product discipline consistently outperform those chasing hacks. That’s why many engineering leaders pair solid writing with measurable distribution and—only where it helps—specialist partners offering <a href="https://techwavespr.com/services/" rel="noopener noreferrer">digital marketing services</a> to keep the pipeline of attention honest and repeatable. This piece distills a pragmatic framework for content that survives scrutiny and compounds over time.

<h2>
 
 
 The Operating Model: From “Post and Pray” to Repeatable Pipelines
</h2>

Great articles don’t appear out of nowhere—they move through a pipeline with explicit gates. Think of it as CI/CD for ideas:

<ul>
<li>Discovery → Drafting → Review → Publish → Observe.</li>
</ul>

At each stage, you’re validating something different: whether the topic matters, whether the draft is clear, whether claims are supported, whether the page renders fast and clean, and how readers actually engage. This isn’t bureaucracy; it’s how you protect your future self from firefighting.

Discovery is about narrowing to problems your readers already feel. The fastest test is to write the problem in one sentence and ask a skeptical colleague if it describes a real moment they’ve lived. If they hesitate, refine until they can retell it in their words.

Drafting prioritizes specificity. Replace abstractions with measurements (“p95 latency dropped from 480 ms to 160 ms”) and name the trade-offs. Engineers recognize truth in constraints. Avoid performative flourishes; ship facts.

Review is a multidisciplinary check: technical accuracy, legal and privacy considerations, and plain-language clarity. The review should be adversarial but bounded—identify a small set of non-negotiables (e.g., security statements must be vetted; benchmarks must be reproducible). Everything else is style, not a blocker.

Publish with a minimum of ceremony but maximum reliability. If your site breaks on mobile, the message never lands. If you embed media, ensure fallbacks. If you annotate with structured data, verify it. This sounds obvious until you audit a few dozen pages and find preventable failures.

Observe like an engineer: define a hypothesis before release (“We expect 40%+ of readers to expand the code sample and average time-on-page of 2:30”), then log events and read them. If the hypothesis fails, write a brief note and iterate. That humility builds more credibility than any slogan.

<h2>
 
 
 Signals That Help Machines and Humans Understand Your Page
</h2>

We don’t have to guess how parsers and browsers treat core elements—there’s public guidance. For example, the robots meta tag is precisely documented by <a href="https://developer.mozilla.org/en-US/docs/Web/HTML/Element/meta/name#robots" rel="noopener noreferrer">MDN Web Docs</a>. Misusing it can quietly hide your excellent work. Likewise, clear directives for crawlers are outlined in Google’s official documentation on <a href="https://developers.google.com/search/docs/crawling-indexing/robots-meta-tag" rel="noopener noreferrer">robots meta directives</a>. You don’t need to become a specialist to benefit: read the short sections relevant to your use case, pick defaults that match your intent (e.g., indexable article pages, non-index utility endpoints), and avoid contradictory signals.

Beyond directives, content earns trust through coherence:

<ul>
<li>
Titles that promise exactly what the body delivers. If the headline says “How We Cut p95 by 3×,” your method and measurement must be visible above the fold.</li>
<li>
Stable URLs. Breaking links is reputational debt. Treat slugs like API versions; change only with migration plans.</li>
<li>
Readable structure. Short paragraphs, code blocks that run, diagrams with alt text, and captions that say what the reader should notice.</li>
<li>
Transparent authorship. A byline with real identity and a sentence on why this person is qualified. Anonymous thought leadership rarely persuades engineers.</li>
</ul>

<h2>
 
 
 The Only Checklist You Actually Need
</h2>

Use this once per article. If you can’t check a box truthfully, fix the cause instead of gaming the symptom.

<ul>
<li>
One-sentence reader problem is clear (share with a skeptic; they should nod).</li>
<li>
Core claim is measurable (numbers, method, and where data lives).</li>
<li>
Page renders fast and clean (mobile first; images sized; no layout shift).</li>
<li>
Directives match intent (no accidental <code>noindex</code>; canonical is correct; no conflicting hints).</li>
<li>
Source links are authoritative (stand on primary docs or peer-reviewed material, not hearsay).</li>
<li>
Reproducibility where relevant (runnable code, version pins, or data snapshot).</li>
<li>
Post-publish hypothesis defined (what success looks like and what you’ll do if it doesn’t happen).</li>
</ul>

Keep this list visible to your team. It’s short on purpose; bloat turns checklists into theater.

<h2>
 
 
 Writing That Respects the Reader’s Time
</h2>

Engineers are allergic to hand-waving. To earn trust, write like you debug:

<ol>
<li>
State the claim. Put the outcome up front. Don’t make people dig.</li>
<li>
Show the path. Provide the minimal context to reproduce. If there are three plausible methods, say why you chose one.</li>
<li>
Expose trade-offs. Every decision has a downside—latency for compute, privacy for convenience, simplicity for flexibility. Calling that out makes the win believable.</li>
<li>
Acknowledge prior art. Name the people and projects you built upon. It’s generous and prevents reinventing the wheel.</li>
<li>
Invite falsification. Offer a way to challenge your result—dataset link, script, or a note on environments where your approach might fail.</li>
</ol>

This style doesn’t just “sound technical.” It protects your team when later decisions reference your document. You’ll thank yourself when a VP says, “Why did we pick this?” and you can point to a paragraph that still holds up.

<h2>
 
 
 Distribution Without the Guilt
</h2>

You don’t need tricks to reach the right readers—you need consistency and fit. Publish where developers already hang out (like Dev.to and your project’s repo), cross-post summaries to communities that value your topic, and keep the voice consistent. Avoid anchor spam and cartoonish calls to action. Invite contact for real reasons: bug reports, benchmarks on different hardware, adoption stories, or counterexamples.

When you link to resources, choose anchors that fit naturally into the sentence. The goal is to be helpful first. Over-optimized phrasing reads strangely to humans and invites the wrong kind of attention from machines. Think of links as citations, not bait.

<h2>
 
 
 Governance: Tiny Rituals That Prevent Big Headaches
</h2>

A lightweight content guild—two to four people who care—can review each draft for clarity, risk, and usefulness. Rotate the “final approver” so the process never bottlenecks. Archive decisions in a living doc: when a topic performed poorly, say so and explain what you learned; when an article exceeded expectations, annotate why (timing, community tie-in, or a strong demo). Over a quarter, this becomes an internal playbook your future teammates will treat as gold.

<h2>
 
 
 The Payoff
</h2>

When you adopt an engineering posture toward content, the benefits accumulate: fewer hotfixes after publish, fewer awkward retractions, more inbound from readers who actually implemented your work, and a library you can confidently resurface months later. Most importantly, you build an audience that trusts you—because your writing respects their time and intelligence.

Bottom line: publish less often, but make each piece unarguably useful. Measure outcomes, admit misses, and iterate in public. That honesty travels further than any tagline.

في عالم إنشاء المحتوى، تعتبر الوضوح والقابلية للتحقق مفتاحًا لكسب الثقة. يبرز هذا المقال أن الفرق التي تتعامل مع النشر كأحد تخصصات المنتج تميل إلى التفوق على تلك التي تعتمد على الحيل السريعة. من خلال الجمع بين الكتابة الجيدة والتوزيع القابل للقياس والتعاون مع شركاء متخصصين عند الحاجة، يمكن لقادة الهندسة إنشاء قناة موثوقة للاهتمام. لا تعزز هذه الطريقة جودة المحتوى فحسب، بل تضمن أيضًا فعاليتها في الوصول إلى الجمهور، مما يجعلها استراتيجية حاسمة للنجاح في المشهد الرقمي اليوم.

En el mundo de la creación de contenido, la claridad y la verificabilidad son clave para ganar confianza. Este artículo enfatiza que los equipos que tratan la publicación como una disciplina de producto tienden a superar a aquellos que dependen de trucos rápidos. Al combinar una escritura sólida con una distribución medible y colaborar con socios especializados cuando es beneficioso, los líderes de ingeniería pueden crear un canal de atención confiable. Este enfoque no solo mejora la calidad del contenido, sino que también asegura su efectividad para llegar a la audiencia, convirtiéndolo en una estrategia crucial para el éxito en el panorama digital actual.

Dans le monde de la création de contenu, la clarté et la vérifiabilité sont essentielles pour gagner la confiance. Cet article souligne que les équipes qui considèrent la publication comme une discipline de produit ont tendance à surpasser celles qui s'appuient sur des astuces rapides. En combinant une rédaction solide avec une distribution mesurable et en collaborant avec des partenaires spécialisés lorsque cela est bénéfique, les leaders en ingénierie peuvent créer un pipeline d'attention fiable. Cette approche améliore non seulement la qualité du contenu, mais garantit également son efficacité pour atteindre le public, ce qui en fait une stratégie cruciale pour réussir dans le paysage numérique d'aujourd'hui.

In the world of content creation, clarity and verifiability are key to earning trust. This article emphasizes that teams treating publishing as a product discipline tend to outperform those relying on quick hacks. By combining solid writing with measurable distribution and collaborating with specialist partners when beneficial, engineering leaders can create a reliable pipeline of attention. This approach not only enhances the quality of content but also ensures its effectiveness in reaching the audience, making it a crucial strategy for success in today's digital landscape.

Build Content Like an Engineer: Systems, Signals, and Checks That Earn Trust

If you've ever seen "TBA/TBA" as a passenger name in a flight booking, it's not a glitch—it's a feature. After booking a cheap group fare on Yatra.com, I discovered the hidden world of airline group bookings, and uncovered a real bug with same-name passengers.

In this post, we'll unpack:

<ul>
<li>How group fare booking systems work</li>
<li>Why "TBA" exists in airline PNRs</li>
<li>What developers building travel systems should know</li>
<li>
A critical bug I found: Same-name passengers causing seat swaps</li>
</ul>




<h2>
 
 
 ✈️ 1. What Are Group Fares?
</h2>

Group fares are special airline rates for 10+ passengers traveling together on the same flight and date.

Common use cases:

<ul>
<li>🏢 Corporate trips</li>
<li>💒 Weddings and family gatherings</li>
<li>🕌 Pilgrimage or religious tours</li>
<li>🏀 School or sports teams</li>
</ul>

Unlike individual bookings, group fares are:

<ul>
<li>
Negotiated directly with airlines or via GDS</li>
<li>More flexible with payment schedules</li>
<li>Allow placeholder names initially</li>
</ul>




<h2>
 
 
 2. Business Logic: The Group Booking Flow
</h2>

Here's how it works from an OTA or travel agent's perspective:

<div class="table-wrapper-paragraph"><table>
<thead>
<tr>
<th>Step</th>
<th>Process</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr>
<td>1️⃣</td>
<td>Group Quote Request</td>
<td>Agency requests fare for route, date, and passenger count</td>
</tr>
<tr>
<td>2️⃣</td>
<td>PNR Creation (TBA stage)</td>
<td>Airline/GDS creates group PNR with placeholders like <code>TBA/TBA</code>
</td>
</tr>
<tr>
<td>3️⃣</td>
<td>Deposit &amp; Hold</td>
<td>Group pays deposit to hold seats</td>
</tr>
<tr>
<td>4️⃣</td>
<td>Name Finalization</td>
<td>12–72 hours before flight, replace "TBA" with real names</td>
</tr>
<tr>
<td>5️⃣</td>
<td>Ticketing</td>
<td>Once names finalized, tickets are issued</td>
</tr>
</tbody>
</table></div>




<h2>
 
 
 📋 3. What Does "TBA" Actually Mean?
</h2>

TBA = To Be Advised

When creating a group booking, actual passenger details may not be known yet.

Example in GDS (Amadeus/Sabre):

Each entry reserves a seat while allowing the agent to:

<ul>
<li>
Hold inventory without final names</li>
<li>
Track blocked seats in airline systems</li>
<li>
Display flight details before passenger confirmation</li>
</ul>

<h4>
 
 
 How GDS Systems Power This Magic
</h4>

Behind the scenes, OTAs don't talk directly to each airline. They use GDS (Global Distribution System) — think of it as the "API gateway" of the travel industry.

The Big Three:

<ul>
<li>
Amadeus (European dominance)</li>
<li>
Sabre (Strong in Americas)</li>
<li>
Travelport (Galileo/Worldspan/Apollo)</li>
</ul>




<h2>
 
 
 ⏰ 4. The 12-Hour Rule
</h2>

Most airlines require final passenger names no later than 12 hours before departure.

What happens at finalization:

<ul>
<li>✅ All "TBA" placeholders updated with real names</li>
<li>⚠️ Unnamed passengers may auto-cancel</li>
<li>🎫 Group PNR transitions to ticketed state</li>
</ul>

This is why Yatra/MMT show "flight details visible before 12 hours" — the system holds the group block, but names are pending.




<h2>
 
 
 5. System Architecture Flow
</h2>

Key technical points:

<ul>
<li>Placeholders stored in PNR until replaced</li>
<li>Airlines track via group booking IDs (not individual tickets)</li>
<li>Background jobs handle PNR sync and updates</li>
</ul>




<h2>
 
 
 💻 6. How OTAs Handle This (Developer View)
</h2>

For platforms like Yatra or MakeMyTrip: 


<div class="highlight js-code-highlight">
<pre class="highlight javascript"><code>// Simplified model
const groupBooking = {
 pnr: "ABC123",
 status: "TBA_PENDING",
 passengers: [
 { firstName: "TBA", lastName: "TBA", title: "MR" },
 { firstName: "TBA", lastName: "TBA", title: "MS" }
 ],
 finalizationDeadline: "2025-11-08T10:00:00Z",
 flightDetails: { visible: false } // visible after name update
};
</code></pre>

</div>



Backend requirements:

<ol>
<li>Handle placeholder data models</li>
<li>Schedule PNR refresh/update jobs</li>
<li>Implement deadline alerts</li>
<li>Validate against duplicate names (see bug below!)</li>
</ol>




<h2>
 
 
 7. CRITICAL BUG I DISCOVERED: Same-Name Collision
</h2>

<h3>
 
 
 The Problem
</h3>

When booking through Yatra's group fare system, I found:

If two passengers have the same name:

<ul>
<li>❌ During web check-in, the system will display both passengers names when the PNR and last name are entered together.</li>
<li>❌ Boarding passes get mixed up</li>
<li>❌ Airport staff can't distinguish passengers</li>
<li>❌ Potential security and check-in issues</li>
</ul>

<h3>
 
 
 Example Scenario
</h3>



<div class="highlight js-code-highlight">
<pre class="highlight javascript"><code>// Booking for two people with same name
passengers: [
 { firstName: "Amit", lastName: "Kumar", seat: "12A" },
 { firstName: "Amit", lastName: "Kumar", seat: "12B" }
]

// What happens in airline system:
// PNR shows: KUMAR/AMIT MR + KUMAR/AMIT MR
// Boarding pass generates wrong seat for one passenger
</code></pre>

</div>



<h3>
 
 
 Why This Happens
</h3>

<ol>
<li>
GDS Name Formatting: Airlines use <code>PNR and LASTNAME</code> combination</li>
<li>
Duplicate Detection: System may treat as duplicate entry</li>
<li>
Seat Assignment Logic: Uses last name as primary key</li>
<li>
Group PNR Merge: Multiple "AMIT KUMAR" entries cause confusion</li>
</ol>

Recommended fixes for OTAs:

<ul>
<li>🔍 Pre-booking validation for duplicate last names</li>
<li>📝 Force middle name or mobile number for duplicates</li>
</ul>




<h2>
 
 
 🔮 8. Future: NDC and Modern APIs
</h2>

IATA's NDC (New Distribution Capability) is modernizing group fares:

<ul>
<li>⚡ Real-time quotes and seat holds</li>
<li>🔄 Easier passenger data updates via REST APIs</li>
<li>📉 Reduced reliance on "TBA" placeholders</li>
<li>🤝 Direct airline-to-OTA connections</li>
</ul>

Though many airlines still support TBA for backward compatibility.




<h2>
 
 
 9. Key Takeaways
</h2>

<div class="table-wrapper-paragraph"><table>
<thead>
<tr>
<th>Point</th>
<th>Reality Check</th>
</tr>
</thead>
<tbody>
<tr>
<td>✅ "TBA" is a feature, not a bug
</td>
<td>Intentional placeholder system for group inventory management</td>
</tr>
<tr>
<td>⏰ The 12-hour rule has a twist
</td>
<td>Names often start reflecting from midnight (not exactly 12 hours), which can frustrate travelers expecting earlier updates</td>
</tr>
<tr>
<td>💰 How OTAs really make money
</td>
<td>Indian OTAs like Yatra/MMT book group fares and mark them up—this is on top of convenience charges. That "cheap fare" might just be a group booking arbitrage</td>
</tr>
<tr>
<td>🚨 Same-name = system chaos
</td>
<td>Multiple passengers with identical last names create PNR conflicts, seat swaps, and boarding issues</td>
</tr>
<tr>
<td>🎭 The agent model
</td>
<td>OTAs aren't always direct airline partners—many operate as super-agents booking group blocks and reselling individually</td>
</tr>
</tbody>
</table></div>




<h2>
 
 
 💬 Discussion
</h2>

For developers building travel systems:

<ol>
<li>How does your system handle group booking placeholders?</li>
<li>Ever encountered the same-name bug I found?</li>
</ol>

Drop your experiences in the comments! 👇




<h2>
 
 
 🔗 Useful Resources
</h2>

<ul>
<li><a href="https://www.iata.org/en/programs/airline-distribution/retailing/ndc/" rel="noopener noreferrer">IATA NDC Program</a></li>
<li><a href="https://developers.amadeus.com/" rel="noopener noreferrer">Amadeus API Documentation</a></li>
<li><a href="https://developer.sabre.com/" rel="noopener noreferrer">Sabre Dev Studio</a></li>
</ul>




This post is based on real-world experience booking through Yatra.com. If you found this helpful, consider sharing it with your travel-tech friends! ✈️




Tags: #traveltech #backend #systemdesign #api #devstory

يتناول المقال عالم حجوزات المجموعات في شركات الطيران، مع التركيز بشكل خاص على التسمية 'TBA/TBA' التي تظهر في حجوزات الرحلات. هذه ليست خللًا، بل ميزة مقصودة تنشأ من تعقيدات حجز أسعار المجموعات. يشارك الكاتب تجارب شخصية من تجربة حديثة مع Yatra.com، موضحًا كيفية عمل هذه الأنظمة للحجز وتأثيراتها على المطورين في صناعة السفر. يمكن أن يساعد فهم ذلك كل من المسافرين والمهنيين في التكنولوجيا على التنقل بشكل أكثر فعالية في تفاصيل السفر الجماعي.

El artículo se adentra en el intrigante mundo de las reservas de grupo de aerolíneas, centrándose específicamente en la designación 'TBA/TBA' que se ve en las reservas de vuelos. Esto no es un error, sino una característica deliberada que surge de las complejidades de reservar tarifas grupales. El autor comparte experiencias personales de una reciente experiencia con Yatra.com, arrojando luz sobre cómo funcionan estos sistemas de reserva y las implicaciones para los desarrolladores en la industria de viajes. Comprender esto puede ayudar tanto a los viajeros como a los profesionales de la tecnología a navegar más eficazmente por las sutilezas de los viajes en grupo.

L'article explore le monde fascinant des réservations de groupe dans les compagnies aériennes, en se concentrant spécifiquement sur la désignation 'TBA/TBA' que l'on voit dans les réservations de vol. Ce n'est pas un bug, mais une fonctionnalité délibérée qui découle des complexités de la réservation de tarifs de groupe. L'auteur partage des expériences personnelles d'une récente expérience avec Yatra.com, éclairant le fonctionnement de ces systèmes de réservation et les implications pour les développeurs de l'industrie du voyage. Comprendre cela peut aider à la fois les voyageurs et les professionnels de la technologie à naviguer plus efficacement dans les nuances des voyages en groupe.

The article delves into the intriguing world of airline group bookings, specifically focusing on the 'TBA/TBA' designation seen in flight reservations. This isn't a glitch but a deliberate feature that arises from the complexities of booking group fares. The author shares personal insights from a recent experience with Yatra.com, shedding light on how these booking systems function and the implications for developers in the travel industry. Understanding this can help both travelers and tech professionals navigate the nuances of group travel more effectively.

How Airline Group Fares Really Work: The Business & Tech Behind 'TBA' Passenger Names

<a href="https://www.techspot.com/news/110174-nearly-2026-most-people-use-123456-password.html" target="_blank"><img src="https://www.techspot.com/images2/news/ts3_thumbs/2025/11/2025-11-07-ts3_thumbs-819.jpg" width="800" height="560" style="padding: 15px 0" title="It's nearly 2026 and most people still use '123456' as a password" /></a> The latest shame-inducing most-common-passwords report comes from tech research and review site Comparitech. Using information leaked on data breach forums in 2025, its researchers aggregated more than 2 billion real account passwords, creating a list of the 100 most-used. <a href="https://www.techspot.com/news/110174-nearly-2026-most-people-use-123456-password.html">Read Entire Article</a>

مع اقتراب عام 2026، يكشف تقرير جديد من Comparitech أن العديد من الأشخاص لا يزالون يعتمدون على كلمات مرور ضعيفة مثل '123456'. هذا أمر مقلق لأنه يسلط الضوء على مشكلة مستمرة في الأمن السيبراني، حيث يفشل الأفراد في اعتماد ممارسات كلمات مرور أقوى على الرغم من التحذيرات المستمرة بشأن خروقات البيانات. إن الاستخدام المستمر لكلمات مرور يسهل تخمينها يعرض المعلومات الشخصية والحساسة للخطر، مما يجعل من الضروري للمستخدمين إعطاء الأولوية لتدابير أمان أفضل.

A medida que nos acercamos a 2026, un nuevo informe de Comparitech revela que muchas personas todavía dependen de contraseñas débiles como '123456'. Esto es preocupante porque resalta un problema persistente en la ciberseguridad, donde los individuos no adoptan prácticas de contraseñas más fuertes a pesar de las advertencias sobre las violaciones de datos. El uso continuo de contraseñas tan fáciles de adivinar pone en riesgo la información personal y sensible, lo que hace crucial que los usuarios prioricen mejores medidas de seguridad.

À l'approche de 2026, un nouveau rapport de Comparitech révèle que de nombreuses personnes continuent de s'appuyer sur des mots de passe faibles comme '123456'. Cela est préoccupant car cela met en lumière un problème persistant en matière de cybersécurité, où les individus ne parviennent pas à adopter des pratiques de mots de passe plus solides malgré les avertissements continus concernant les violations de données. L'utilisation continue de mots de passe aussi facilement devinables met en danger les informations personnelles et sensibles, rendant crucial pour les utilisateurs de donner la priorité à de meilleures mesures de sécurité.

As we approach 2026, a new report from Comparitech reveals that many people still rely on weak passwords like '123456'. This is concerning because it highlights a persistent issue in cybersecurity, where individuals fail to adopt stronger password practices despite ongoing warnings about data breaches. The continued use of such easily guessable passwords puts personal and sensitive information at risk, making it crucial for users to prioritize better security measures.

It's nearly 2026 and most people still use '123456' as a password

You know those “we migrated and everything is 10x faster” posts that leave out the messy bits? This isn’t one of them.

I'm a data engineer working in financial services, partnering with Palantir on one of our in-house strategic platforms*. Big, distributed data is part of the day job, so PySpark is the comfortable hoodie we’ve worn for years. But here’s the plot twist: for our small to mid-sized datasets (think: tens of MBs to a few GBs, not petabytes), we started swapping PySpark pipelines for Polars. And the dev loop went from coffee-break to “wait, it’s done?”

Let me tell you how that happened, where Polars shines, where Spark still wins, and exactly how to translate those “Spark-isms” you’ve internalized into Polars without wanting to throw your laptop.

<blockquote>
*Disclaimer: The code and project shown here are my personal work and are not affiliated with, endorsed by, or the property of my employer.
</blockquote>




<h3>
 
 
 TL;DR (for the colleague skimming this on a train)
</h3>

Polars vs PySpark for small to mid-sized data: Polars’ Rust engine, lazy evaluation, and expression API deliver faster runtimes and quicker iteration on a single machine. Keep Spark for cluster-scale workloads, governed lakehouse writes, and production streaming. For migration, replace UDFs with expressions, lean on <code>join_asof</code>, <code>group_by_dynamic</code>, <code>struct/list</code> ops, and <code>sink_parquet()</code> for outputs.




<h4>
 
 
 The short version (so you can send this to your team chat)
</h4>

<ul>
<li>If your data fits on a single beefy machine, Polars will often run circles around PySpark and make your codebase smaller.</li>
<li>When you actually need a cluster, a metastore, ACID lakehouse writes, or battle-hardened streaming semantics, Spark is still your friend.</li>
<li>The switch is less painful than you think. Expressions &gt; UDFs, embrace lazy queries, and learn three or four Polars-specific tricks (as-of joins, dynamic windows, struct/list ops).</li>
</ul>




<h4>
 
 
 A quick story from the trenches
</h4>

We had a workforce modeling DAG that joined dimension tables, applied a thicket of conditional business rules, and rolled up time-based metrics. In PySpark, the job was fine, just… ritualistic: spin a session, serialize UDFs, wait out the cluster shuffle tax, and go stare out the window while Catalyst did its thing. 
One day we rewrote the same pipeline in Polars with lazy scans and expressions. No UDFs. No session boot. Same logic, fewer lines. The run finished before the “I’ll grab a coffee” instinct completed. The drama? The cluster didn’t even get invited to the meeting.


<h4>
 
 
 Why Polars works so well on “normal-sized” data
</h4>

<ul>
<li>
It’s Rust under the hood. Vectorized, multi-threaded, cache-friendly. Python just orchestrates expressions.</li>
<li>
Lazy by default (when you choose it). You build a plan (<code>scan_parquet</code> -&gt; <code>transforms</code> -&gt; <code>collect()</code>), and Polars fuses steps to avoid unnecessary passes.</li>
<li>
Expression API beats UDFs. The minute your logic is expressible, you stop paying Python &lt;-&gt; JVM costs and serialization overhead.</li>
</ul>


<h3>
 
 
 The non-obvious differences that actually matter
</h3>

<a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2F5ac88h07qyndxp2remw5.png" class="article-body-image-wrapper"><img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2F5ac88h07qyndxp2remw5.png" alt="polars vs pyspark" width="800" height="439"></a>


<h3>
 
 
 “But Spark can do X and I don’t see it in Polars…” (Here’s how to do it)
</h3>

Below are the patterns we actually used while migrating pipelines.

1. Time-range join (point-in-time lookup) 


<div class="highlight js-code-highlight">
<pre class="highlight plaintext"><code># PySpark
from pyspark.sql import functions as F, Window as W

# For each event, attach the most recent dimension row effective &lt;= event.ts
cond = [events.abc == dim.abc, events.ts &gt;= dim.eff_ts]
joined = (events.join(dim, cond, "left")
 .withColumn("rn", F.row_number().over(
 W.partitionBy("event_id").orderBy(F.col("dim.eff_ts").desc())
 ))
 .filter("rn=1").drop("rn"))

# --- same idea in Polars ---
# Polars
import polars as pl

events = pl.scan_parquet("events.parquet")
dim = pl.scan_parquet("dim.parquet")

# Natural fit: as-of join on timestamp with a key
out = events.join_asof(
 dim, on="ts", by="abc", strategy="backward", tolerance="5m"
).collect()
</code></pre>

</div>



<blockquote>
When <code>join_asof</code> isn’t enough (e.g., need <code>ts BETWEEN start AND end</code>): pre-expand dimension rows into <code>(start, end)</code> boundaries and filter after a cheap join: 

</blockquote>

<div class="highlight js-code-highlight">
<pre class="highlight plaintext"><code># Small dim? Cross then filter (ok for small) or prebucket by day.
out = (events.join(dim, on="abc", how="left")
 .filter((pl.col("ts") &gt;= pl.col("start")) &amp; (pl.col("ts") &lt; pl.col("end")))
 .with_columns(
 pl.col("ts").sort_by("ts").over("event_id") # keep stability if needed
 )
 ).collect()
</code></pre>

</div>



2. Complex conditional with many CASE WHENs 


<div class="highlight js-code-highlight">
<pre class="highlight plaintext"><code># PySpark
from pyspark.sql import functions as F

df = df.withColumn(
 "final_score",
 F.when(F.col("score") &gt;= 90, "A")
 .when(F.col("score") &gt;= 75, "B")
 .when((F.col("score") &gt;= 60) &amp; (F.col("region") == "Lake Region"), "C+")
 .otherwise("C")
)

# --- same idea in Polars ---
# Polars
import polars as pl

df = df.with_columns([
 pl.when(pl.col("score") &gt;= 90).then("A")
 .when(pl.col("score") &gt;= 75).then("B")
 .when((pl.col("score") &gt;= 60) &amp; (pl.col("region") == "Lake Region")).then("C+")
 .otherwise("C")
 .alias("final_score")
])
</code></pre>

</div>



<blockquote>
The nested <code>when/then/otherwise</code> in Polars is ergonomic and compiles into a single expression tree.
</blockquote>

3. “Collect a struct, then explode it later” 


<div class="highlight js-code-highlight">
<pre class="highlight plaintext"><code>#PySpark
aggd = (df.groupBy("forest")
 .agg(F.collect_list(F.struct("region","place")).alias("full_place")))
flat = aggd.select("forest", F.explode_outer("full_place").alias("p")).select("forest","p.*")

# --- same idea in Polars ---
# Polars
aggd = (df.group_by("forest")
 .agg(pl.struct(["region","place"]).list().alias("full_place")))

flat = (aggd
 .with_columns(pl.col("full_place").explode())
 .unnest("full_place"))
</code></pre>

</div>



<blockquote>
<code>unnest</code> on <code>struct</code> is a great trick: no manual field projection necessary.
</blockquote>

4. Rolling window over time with business calendars 


<div class="highlight js-code-highlight">
<pre class="highlight plaintext"><code>#PySpark
from pyspark.sql import functions as F, Window as W

w = W.partitionBy("abc").orderBy("ts").rowsBetween(-6, 0)
out = df.withColumn("w7", F.avg("value").over(w))

# --- same idea in Polars ---
# Polars
out = (df.sort(["abc","ts"])
 .with_columns(
 pl.col("value").rolling_mean(window_size=7).over("abc").alias("w7")
 ))
</code></pre>

</div>



<blockquote>
If your index is a timestamp with irregular spacing, reach for <code>group_by_dynamic</code>: 

</blockquote>

<div class="highlight js-code-highlight">
<pre class="highlight plaintext"><code>roll = (df.group_by_dynamic(index_column="ts", every="1w", period="1w", by="abc")
 .agg(pl.col("value").mean().alias("w7")))
</code></pre>

</div>



5. Broadcast a tiny dimension without… a hint 


<div class="highlight js-code-highlight">
<pre class="highlight plaintext"><code>#PySpark
small_dim = spark.table("dim_small")
df = df.hint("broadcast").join(small_dim, "key", "left")

# --- same idea in Polars ---
# Polars
# Just join. If the right side is tiny, Polars keeps it in memory.
df = df.join(small_dim, on="key", how="left")
</code></pre>

</div>



<blockquote>
No hint needed on a single machine; Polars will do the sensible thing.
</blockquote>




<h4>
 
 
 Where we still reach for Spark
</h4>

<ul>
<li>
Data too big for one box. If your joins or shuffles exceed a single host’s RAM/IO comfort zone, you want a cluster.</li>
<li>
Lakehouse governance. Need native Delta/Iceberg writes with compaction, vacuuming, and a metastore? Spark’s the grown-up in the room.</li>
<li>
Production streaming semantics. Exactly-once sinks, watermarking across stateful operators — Spark’s Structured Streaming is still the benchmark.</li>
</ul>




<h4>
 
 
 A tiny migration playbook (what we actually did)
</h4>

<ol>
<li>
Start lazy. Prefer <code>pl.scan_parquet(...)</code> -&gt; <code>transform</code> -&gt; <code>collect()/sink_parquet()</code>.</li>
<li>
Delete UDFs. If you’re writing Python UDFs in Spark, translate them into expressions in Polars. It’s almost always possible.</li>
<li>
Explode early, unnest often. Nested data becomes readable with <code>unnest</code>, <code>explode</code>, <code>arr ops</code>.</li>
<li>
Test with golden data. Same sample through both engines; compare row counts, sums, and a few canonical hashes.</li>
<li>
Keep Spark for the big guns. Don’t martyr yourself trying to force a 2-TB join into one box.</li>
</ol>




<h4>
 
 
 Two-step migration (no drama version)
</h4>

Step 1: Like-for-like swap. We replaced PySpark with Polars while keeping the business logic identical. Built the plan with <code>scan_*</code> + expressions, then checked parity with row counts, hashes, and a few KPI spot checks. Goal: prove equivalence, not chase speed. 
Step 2: Optimize for Polars. We refactored to lean on lazy evaluation and vectorized expressions, trimmed intermediates, and ditched Python UDFs. 
The payoff came in two clean drops: first from shedding distributed overhead (think ~5 -&gt; ~2 minutes), then to consistently sub-minute after the Polars-native rewrite. Fewer lines, steadier memory, snappier UI.




<h4>
 
 
 Gotchas we hit (so you don’t)
</h4>

<ul>
<li>
Null propagation: Polars is strict. Use <code>fill_null</code>, <code>coalesce</code> (<code>pl.coalesce([colA, colB])</code>) intentionally.</li>
<li>
Types are not vibes. Specify <code>dtype</code> on read if your CSVs are “creative.”</li>
<li>
Non-equi joins: Reach for <code>join_asof</code> or filter-after-join patterns. If it looks like a cross join… it is a cross join—use it sparingly.</li>
<li>
Don’t <code>apply</code> unless you must. If you write a Python lambda over rows, you’re leaving performance on the floor. Stick to expressions.</li>
</ul>




<h4>
 
 
 What I’d do on Monday
</h4>

Pick a pipeline under a few GB, port the transforms you can without UDFs, wire up <code>scan_*</code> -&gt; <code>expressions</code> -&gt; <code>collect()/sink_parquet()</code>, and compare outputs. If your run time drops and your code shrinks, congratulations! You just freed up time for the hard problems. 
If it doesn’t? That probably means you genuinely need Spark’s distributed muscle. Use the right tool and move on with your life.

في تناول منعش لمعالجة البيانات، يشارك مهندس بيانات في قطاع الخدمات المالية تجربته في الانتقال من PySpark إلى Polars للتعامل مع مجموعات بيانات أصغر. أدى هذا التغيير إلى تحسينات كبيرة في الأداء، مما جعل عمله أكثر كفاءة ومتعة. يبرز المقال أهمية تكييف الأدوات لتناسب الاحتياجات المحددة، خاصة عند التعامل مع أحجام بيانات أصغر، ويعمل كتذكير بأن الابتعاد أحيانًا عن العادات المألوفة يمكن أن يؤدي إلى نتائج أفضل.

En un enfoque refrescante sobre el procesamiento de datos, un ingeniero de datos del sector de servicios financieros comparte su experiencia al cambiar de PySpark a Polars para manejar conjuntos de datos más pequeños. Este cambio ha llevado a mejoras significativas en el rendimiento, haciendo su trabajo más eficiente y agradable. El artículo destaca la importancia de adaptar las herramientas a necesidades específicas, especialmente al tratar con volúmenes de datos más pequeños, y sirve como un recordatorio de que a veces, alejarse de hábitos familiares puede conducir a mejores resultados.

Dans une approche rafraîchissante du traitement des données, un ingénieur en données du secteur des services financiers partage son expérience de passage de PySpark à Polars pour gérer des ensembles de données plus petits. Ce changement a entraîné des améliorations de performance significatives, rendant son travail plus efficace et agréable. L'article souligne l'importance d'adapter les outils aux besoins spécifiques, surtout lorsqu'il s'agit de volumes de données plus petits, et rappelle que parfois, s'éloigner des habitudes familières peut conduire à de meilleurs résultats.

In a refreshing take on data processing, a data engineer in the financial services sector shares their experience of switching from PySpark to Polars for handling smaller datasets. This change has led to significant performance improvements, making their work more efficient and enjoyable. The article highlights the importance of adapting tools to fit specific needs, especially when dealing with smaller data volumes, and serves as a reminder that sometimes, stepping away from familiar habits can lead to better outcomes.

We Stopped Reaching for PySpark by Habit. Polars Made Our Small Jobs Boringly Fast.

Another broad selloff that dented high-flying AI trades from Nvidia Corp. to Palantir Technologies Inc. left an old stalwart of the tech sector unscathed: Apple Inc.

تمكنت شركة آبل من الحفاظ على مكانتها القوية في قطاع التكنولوجيا على الرغم من عمليات البيع الواسعة التي أثرت على أسهم الذكاء الاصطناعي مثل نيفيديا وبالانتير. تسلط هذه المرونة الضوء على مكانة آبل كملاذ آمن للمستثمرين، خاصة في ظروف السوق غير المستقرة. بينما تواجه تداولات الذكاء الاصطناعي تقلبات، توفر استقرار آبل تباينًا مريحًا، مما يجعلها لاعبًا رئيسيًا يجب مراقبته في المشهد التكنولوجي المتطور.

Apple Inc. ha logrado mantener su sólida posición en el sector tecnológico a pesar de una reciente venta masiva que afectó a acciones de IA como Nvidia y Palantir. Esta resiliencia destaca el estatus de Apple como un refugio seguro para los inversores, especialmente en condiciones de mercado inciertas. A medida que las operaciones de IA enfrentan volatilidad, la estabilidad de Apple ofrece un contraste tranquilizador, convirtiéndola en un jugador clave a seguir en el paisaje tecnológico en evolución.

Apple Inc. a réussi à maintenir sa position forte dans le secteur technologique malgré une récente vente massive touchant des actions d'IA comme Nvidia et Palantir. Cette résilience souligne le statut d'Apple en tant que refuge sûr pour les investisseurs, surtout dans des conditions de marché incertaines. Alors que les échanges d'IA font face à la volatilité, la stabilité d'Apple offre un contraste rassurant, en faisant un acteur clé à surveiller dans le paysage technologique en évolution.

Apple Inc. has managed to maintain its strong position in the tech sector despite a recent selloff affecting AI stocks like Nvidia and Palantir. This resilience highlights Apple's status as a safe haven for investors, especially in uncertain market conditions. As AI trades face volatility, Apple's stability offers a reassuring contrast, making it a key player to watch in the evolving tech landscape.

Apple Regains Safe-Haven Status as AI Trade Looks Shakier

Global AI semiconductor company DEEPX (CEO Lokwon Kim) announced that it has won two CES 2026 Innovation Awards, while Sixfab, a US-based IoT and edge computing company, received the Best of Innovation award — CES&#8217;s highest honor — for its AI gateway ALPON X5 powered by DEEPX&#8217;s DX-M1. This milestone demonstrates how DEEPX&#8217;s solutions are...
The post <a href="https://ai-techpark.com/deepx-wins-two-ces-2026-awards-powers-sixfab-alpon-x5/">DEEPX Wins Two CES 2026 Awards; Powers Sixfab ALPON X5</a> first appeared on <a href="https://ai-techpark.com">AI-Tech Park</a>.

حققت DEEPX إنجازًا كبيرًا بفوزها بجائزتين مرموقتين في جوائز CES 2026، مما يبرز تقنيتها المتقدمة في أشباه الموصلات الذكية. لا تبرز هذه الجائزة التزام DEEPX بالابتكار فحسب، بل تسلط الضوء أيضًا على تأثير تعاونها مع Sixfab، التي حصلت على جائزة أفضل ابتكار لجهازها البوابة الذكية ALPON X5. يجسد هذا التعاون كيف يمكن للتكنولوجيا المتقدمة أن تدفع التقدم في مجالات إنترنت الأشياء والحوسبة الطرفية، مما يمثل علامة فارقة مهمة لكلتا الشركتين.

DEEPX ha captado la atención al ganar dos prestigiosos premios de innovación en CES 2026, destacando su tecnología de semiconductores de IA de vanguardia. Este reconocimiento no solo resalta el compromiso de DEEPX con la innovación, sino también el impacto de su colaboración con Sixfab, que recibió el premio al mejor de la innovación por su puerta de enlace de IA, el ALPON X5. Esta asociación ejemplifica cómo la tecnología avanzada puede impulsar el progreso en los sectores de IoT y computación en el borde, marcando un hito significativo para ambas empresas.

DEEPX a fait sensation en remportant deux prix prestigieux lors des CES 2026, mettant en avant sa technologie de semi-conducteurs AI de pointe. Cette reconnaissance souligne non seulement l'engagement de DEEPX envers l'innovation, mais aussi l'impact de sa collaboration avec Sixfab, qui a reçu le prix du meilleur de l'innovation pour sa passerelle AI, l'ALPON X5. Ce partenariat illustre comment la technologie avancée peut stimuler le progrès dans les secteurs de l'IoT et de l'informatique en périphérie, marquant ainsi une étape importante pour les deux entreprises.

DEEPX has made headlines by winning two prestigious CES 2026 Innovation Awards, showcasing its cutting-edge AI semiconductor technology. This recognition not only highlights DEEPX's commitment to innovation but also underscores the impact of its collaboration with Sixfab, which received the Best of Innovation award for its AI gateway, the ALPON X5. This partnership exemplifies how advanced technology can drive progress in the IoT and edge computing sectors, making it a significant milestone for both companies.

DEEPX Wins Two CES 2026 Awards; Powers Sixfab ALPON X5

Tektome, a next-generation AI solutions provider for the architecture, engineering and construction (AEC) industry, today announced the official release of&#160;KnowledgeBuilder, an AI-powered solution that transforms past project data into structured design intelligence. The new tool helps AEC teams convert decades of drawings, reports, photos, and even handwritten notes into a...
The post <a href="https://ai-techpark.com/tektome-launches-knowledgebuilder-ai-for-design-intelligence/">Tektome Launches KnowledgeBuilder AI for Design Intelligence</a> first appeared on <a href="https://ai-techpark.com">AI-Tech Park</a>.

أطلقت شركة تيكتوم KnowledgeBuilder، وهي أداة ذكاء اصطناعي مبتكرة مصممة لإحداث ثورة في صناعة الهندسة المعمارية والهندسة والبناء (AEC). تأخذ هذه الحلول القوية سنوات من بيانات المشاريع—مثل الرسومات والتقارير وحتى الملاحظات المكتوبة بخط اليد—وتحولها إلى ذكاء تصميم منظم. هذا الأمر مهم لأنه لا يسهل فقط عملية التصميم، بل يساعد الفرق أيضًا على الاستفادة من التجارب السابقة لتحسين المشاريع المستقبلية، مما يجعلها نقطة تحول للمحترفين في هذا المجال.

Tektome ha lanzado KnowledgeBuilder, una herramienta de IA innovadora diseñada para revolucionar la industria de la arquitectura, la ingeniería y la construcción (AEC). Esta poderosa solución toma años de datos de proyectos—como dibujos, informes e incluso notas manuscritas—y los transforma en inteligencia de diseño estructurada. Esto es significativo porque no solo agiliza el proceso de diseño, sino que también ayuda a los equipos a aprovechar experiencias pasadas para mejorar proyectos futuros, convirtiéndose en un cambio radical para los profesionales del sector.

Tektome vient de lancer KnowledgeBuilder, un outil d'IA innovant conçu pour révolutionner l'industrie de l'architecture, de l'ingénierie et de la construction (AEC). Cette solution puissante prend des années de données de projets—comme des dessins, des rapports et même des notes manuscrites—et les transforme en intelligence de conception structurée. Cela est important car cela simplifie non seulement le processus de conception, mais aide également les équipes à tirer parti des expériences passées pour améliorer les projets futurs, ce qui en fait un changement de jeu pour les professionnels du secteur.

Tektome has just launched KnowledgeBuilder, an innovative AI tool designed to revolutionize the architecture, engineering, and construction (AEC) industry. This powerful solution takes years of project data—like drawings, reports, and even handwritten notes—and transforms it into structured design intelligence. This is significant because it not only streamlines the design process but also helps teams leverage past experiences to enhance future projects, making it a game-changer for professionals in the field.

Tektome Launches KnowledgeBuilder AI for Design Intelligence

Built by former Databricks and Apple engineers, OpenPCC enables companies to safely use large language models without exposing confidential or personal information Confident Security today released OpenPCC, the first open-source standard that allows companies to use large language models (LLMS) without exposing sensitive data. Built by engineers from Databricks and Apple,...
The post <a href="https://ai-techpark.com/confident-security-launches-openpcc-to-protect-ai-shared-data/">Confident Security Launches OpenPCC to Protect AI-Shared Data</a> first appeared on <a href="https://ai-techpark.com">AI-Tech Park</a>.

أطلقت شركة Confident Security OpenPCC، وهو معيار مفتوح المصدر مصمم لمساعدة الشركات على استخدام نماذج اللغة الكبيرة مع حماية البيانات الحساسة. تم تطويره بواسطة فريق من المهندسين السابقين في Databricks وApple، هذه الأداة مهمة لأنها تعالج المخاوف المتزايدة بشأن خصوصية البيانات في تطبيقات الذكاء الاصطناعي. من خلال تمكين الاستخدام الآمن للبيانات، لا يعزز OpenPCC الثقة في تقنيات الذكاء الاصطناعي فحسب، بل يمكّن أيضًا الشركات من الاستفادة من قدرات الذكاء الاصطناعي المتقدمة دون المساس بالسرية.

Confident Security ha lanzado OpenPCC, un estándar de código abierto innovador diseñado para ayudar a las empresas a utilizar modelos de lenguaje grandes mientras protegen los datos sensibles. Desarrollado por un equipo de antiguos ingenieros de Databricks y Apple, esta herramienta es crucial ya que aborda las crecientes preocupaciones sobre la privacidad de los datos en las aplicaciones de IA. Al permitir el uso seguro de datos, OpenPCC no solo mejora la confianza en las tecnologías de IA, sino que también empodera a las empresas para aprovechar las capacidades avanzadas de la IA sin comprometer la confidencialidad.

Confident Security a lancé OpenPCC, une norme open-source innovante conçue pour aider les entreprises à utiliser des modèles de langage tout en protégeant les données sensibles. Développé par une équipe d'anciens ingénieurs de Databricks et d'Apple, cet outil est crucial car il répond aux préoccupations croissantes concernant la confidentialité des données dans les applications d'IA. En permettant une utilisation sécurisée des données, OpenPCC renforce non seulement la confiance dans les technologies d'IA, mais permet également aux entreprises de tirer parti des capacités avancées de l'IA sans compromettre la confidentialité.

Confident Security has launched OpenPCC, an innovative open-source standard designed to help companies utilize large language models while safeguarding sensitive data. Developed by a team of former engineers from Databricks and Apple, this tool is crucial as it addresses the growing concerns around data privacy in AI applications. By enabling secure data usage, OpenPCC not only enhances trust in AI technologies but also empowers businesses to leverage advanced AI capabilities without compromising confidentiality.

Seekr Appoints Ex-Palantir Exec Lloyd Cope as CRO

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