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High-quality switch supplier invites you to cooperate
Dear Info,
We are a leading high-quality switch manufacturer. With many years of industry experience and high-quality products, we serve many partners around the world and are widely praised.
Our core products:
Micro switch: high sensitivity, suitable for electrical appliances, automobiles, industrial equipment, medical and other industries;
Rocker switch: diversified design to meet different needs;
Push button switch: durable, widely used in a variety of industries;
Keyboard switch: comfortable feel, designed for user experience.
Our factory has passed ISO certification and provides fast delivery, OEM/ODM services, and can tailor solutions according to your specific needs.
I hope to have the opportunity to understand your company's needs and explore the possibility of cooperation. If you need samples or quotations, please feel free to contact me and I will provide you with detailed information.
Best regards&Thanks
David Wu
Yueqing Tongda Wire Electric Factory
ADD:No.8 Chuanger Road,Yuqing Bay Port Area, Wenzhou,Zhejiang,325609
Tel: 0086-577 57158583
Mobil: 0086-13780102300
Web: www.chinaweipeng.com
Mail: wdm@tdweipeng.com(If email Failed, pls send to weipeng@tdweipeng.com)
Made-In-China: tongdaswitch.en.made-in-china.com
by "Momen Slama" <momenslama451@gmail.com> - 10:01 - 10 Jun 2025 -
Professional Solutions to Cutting Challenges in the Building Decoration Industry
Dear Info,I'm Xavier from Koocut Cutting Technology (Sichuan) Co., Ltd. Our company has extensive experience in the cutting - tool industry, thanks to the technical accumulation of our parent company over the past two decades.In the building decoration industry, precision and efficiency are of utmost importance. Our PCD cement - fiber - board - processing circular saw blades and TCT color - steel - plate - processing circular saw blades are specifically designed to address the cutting challenges in this field. These blades can cut various building materials with high precision, resulting in smooth edges and minimal waste.Our factory, operating in line with Industry 4.0 standards, features intelligent and flexible production capabilities. This means we can quickly adjust production according to your specific order requirements, whether it's a small - batch customized order or a large - scale standard order. We also have a strict quality control system to ensure that every product leaving our factory meets the highest quality standards.We've already worked with many building decoration service providers globally, helping them improve project efficiency and customer satisfaction. We believe we can do the same for your company. If you have any questions or are interested in our products, please contact me.Best regards,
Contact Information:
WhatsApp:+86 17388372772
Email: xavier@koocut.comKoocut Cutting Technology (Sichuan) Co., Ltd.
by "Beaner Lovely" <beanerlovely@gmail.com> - 09:59 - 10 Jun 2025 -
LIVE from Info-Tech (and what’s actually being said)
LIVE from Info-Tech (and what’s actually being said)
Hi MD Abul,
Greg Benton here, Chief Strategy Officer at Third Stage. Eric couldn’t make it to this year’s Info-Tech LIVE conference, so I’m stepping in to share a few thoughts from the ground.
I’m writing this from a hotel lobby, half-empty coffee in hand, name badge already flipped backward, and that familiar buzz of conference energy all around.
We’re here at Info-Tech LIVE, and like always, it’s impressive.
Screens glowing. AI demos everywhere. Consultants are speed-walking to the next panel. Booths promising transformation in bold letters.
But here’s the thing that always hits me in moments like this:
You can feel the gap between the noise and the real work.Because while the tech looks great on the showroom floor, most of the conversations that matter? They’re happening off to the side. In quiet 1-on-1s. At the coffee stations. In the space between hype and execution.
Earlier today, someone asked me what I’m most excited about in the AI space.
And honestly?
It’s not the tools. It’s the teams finally asking better questions.
Not “What can this new system do?”
But:-
“How do we need to change to actually use this?”
-
“Are our people ready?”
-
“Is this even solving the right problem?”
That’s the shift we’re seeing, the one that actually moves companies forward.
We’ll be here all week, walking the floor, sitting in on sessions, and having the real conversations that don’t fit in a glossy brochure. If you’re here too, come say hi.
And if you’re not, don’t worry. We’ll bring the takeaways back with us.
That’s exactly what our Digital Stratosphere Conference this August is all about. We’re pulling back the curtain on strategy, systems, and what it takes to make AI and digital transformation work in the real world, not just the keynote stage.
Our theme this year is Mission: AI-Possible, and we’d love to see you there.
Use the code "earlybird" for 20% off your ticket(s)!
Best regards,
Greg Benton
by "Greg Benton" <greg.benton@thirdstage-consulting.com> - 09:31 - 10 Jun 2025 -
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Premium nutritional ingredients you are looking for——in stock in our US warehouse
Dear Info,
Glad to noticed that you are in Dietary Supplements contract manufacturing field in US. Hope this email is helpful for your procurement.
I 'm from Shaanxi Top purity Biotech Ltd. We are a manufacturer of nutritional supplements in China, with a warehouse in California.Our product is factory direct sales, with stable output and favorable prices.
We have been engaged in trading in nutraceutical for over 10 years ,our products have been audited and approved by worldwide reputed customers, such as Glanbia, Nestlé, PIPING ROCK, NBTY, Pharmavite, Now foods, Nutricost, Robinson pharma.
If you want to purchase any Herbs & Botanicals ingredients ,Protein Powders, Probiotics, Enzymes and Specialty products, please feel free to let me know.
Below are our current hot sale products for better check. I believe it will definitely help you save a lot of purchasing costs.
Should you any interest, please feel free to let me know.
Warehouse Add:13735 iroquois Pl,Chino ,CA,91710
Description
Qty (By Kg)
Price（USD/Kg)
Cascara Sagrada Powder
950
9
D-Biotin Tianxin
233
160
Deer Antler Extract 4:1
125
45
Deer Antler powder
275
55
Devil’s Claw root powder
200
8
Diosmin Complex 90% (80%Diosmin&10% Hesperidin)
275
55
Echinacia extract
975
8
Epicatechin 90%
50
200
Fish Collagen
500
18
Forsythia Extract 5-1
350
8
HICA;Alpha-hydroxy-isocaproate Calcium
25
40
Huperzine A 1%
7
500
Inositol -Myo
4500
8
Ipriflavone
100
98
Irish moss powder
300
8
Jambolan Powder
25
10
kale powder
500
5
Ledebouriella Divarciata Extract 5-1
275
8
L-Glutathione Reduced
75
75
Ligusticum Wallichilrhizone Powder
50
8
Maca Extract
225
8
Maca Gelatinized Powder
1000
8
Melatonin
230
72
Milk Thistle Extract 80%
500
30
MK4 1%
81
100
Motherwort Powder
300
5
Mulberry Leaf extract
100
8
Neem Leaf Extract
50
9
Nicotinamide Adenine Dinucleotide 99% (NAD)
300
130
NMN-β-nicotinamide mononucleotide
175
95
Passion Flower Powder
25
8
PHOSPHATIDYLSERINE 20%
25
55
Pterostilbene
20
300
PYRROLOQUINOLINE QUINONE DISODIUM SALT
10
1100
Quercetin Dihydrate powder 95%
700
48
Resveratrol 20%
25
40
Rhodiola Rosea P.E. (Rosavins 3% Salidroside 1%)
75
145
Rutin 95% NF 11
750
28
Saffron Extract 0.3%
25
120
Schisandra Extract 2% HPLC
50
34
Schisandra Extract 4:1
150
8
Schisandra P.E. 2% UV
25
8
Sea -Buckthorn Powder
50
10
Shilajit Extract 20%
100
35
SOD(8000IU )
535
55
Sodium copper chlorophyllin
100
200
Sodium Hyaluronate Haiber
1800
82
Sucralose Techno /jinhe
1800
23
Theobromine 99%
500
47
TUDCA
205
350
Best regards,
Top purity sales team
What's App: 44 7463 099214
Wechat: 17729507767
DL: 1 909-516-8031 / 1 909-678-6521
e-mail: sales3@toppuritybio.com;sales4@sinoingredients.online
by "Biljana Lebowski" <biljanalebowski743@gmail.com> - 05:25 - 10 Jun 2025 -
Cost-Effective Performance
Dear Info,
Balancing performance and cost is critical in the UAV industry. At Micro Magic Inc, we provide high-precision inertial sensors that deliver exceptional value without compromising on quality. Our cost-effective solutions are trusted by leading drone manufacturers worldwide.
Interested in learning more? Let’s arrange a call to discuss further.
Best regards,
Young
Account Manager
Micro Magic Inc
Skypy: manot27
Whatsapp: +8618151836753
Website: www.memsmag.com
by "Karaeski Martirosov" <martirosovkaraeski804@gmail.com> - 12:55 - 10 Jun 2025 -
How Lyft Uses ML to Make 100 Million Predictions A Day
How Lyft Uses ML to Make 100 Million Predictions A Day
Forwarded this email? Subscribe here for moreDatabase Benchmarking for Performance: Virtual Masterclass (Sponsored)
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After this free 2-hour masterclass, you will know how to:
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Disclaimer: The details in this post have been derived from the articles/videos shared online by the Lyft Engineering Team. All credit for the technical details goes to the Lyft Engineering Team. The links to the original articles and videos are present in the references section at the end of the post. We’ve attempted to analyze the details and provide our input about them. If you find any inaccuracies or omissions, please leave a comment, and we will do our best to fix them.
Hundreds of millions of machine learning inferences power decisions at Lyft every day. These aren’t back-office batch jobs. They’re live, high-stakes predictions driving every corner of the experience from pricing a ride to flagging fraud, predicting ETAs to deciding which driver gets which incentive.
Each inference runs under pressure and a single-digit millisecond budget. This translates to millions of requests per second. Dozens of teams, each with different needs and models, are pushing updates on their schedules. The challenge is staying flexible without falling apart.
Real-time ML at scale breaks into two kinds of problems:
Data Plane pressure: Everything that happens in the hot path. This includes CPU and memory usage, network bottlenecks, inference latency, and throughput ceilings.
Control Plane complexity: This is everything around the model. Think of aspects like deployment and rollback, versioning, retraining, backward compatibility, experimentation, ownership, and isolation.
Early on, Lyft leaned on a shared monolithic service to serve ML models across the company. However, the monolith created more friction than flexibility. Teams couldn’t upgrade libraries independently. Deployments clashed and ownership blurred. Small changes in one model risked breaking another, and incident investigation turned into detective work.
The need was clear: build a serving platform that makes model deployment feel as natural as writing the model itself. It had to be fast, flexible, and team-friendly without hiding the messy realities of inference at scale.
In this article, we’ll look at how Lyft built an architecture to accomplish this requirement and the challenges they faced.
Architecture and System Components
LyftLearn Serving doesn’t reinvent the wheel. It slots neatly into the microservices foundation already powering the rest of Lyft. The goal wasn’t to build a bespoke ML serving engine from scratch. It was to extend proven infrastructure with just enough intelligence to handle real-time inference, without bloating the system or boxing teams.
At the core is a dedicated microservice: lightweight, composable, and self-contained. Each team runs its instance, backed by Lyft's service mesh and container orchestration stack. The result: fast deploys, predictable behavior, and clean ownership boundaries.
Let’s break down this architecture flow diagram:
HTTP Serving Layer
Every request to a LyftLearn Serving service hits an HTTP endpoint first. This interface is built using Flask, a minimalist Python web framework. While Flask alone wouldn’t scale to production workloads, it’s paired with Gunicorn, a pre-fork WSGI server designed for high concurrency.
To make this stack production-grade, Lyft optimized the setup to align with Envoy, the service mesh that sits in front of all internal microservices. These optimizations ensure:
Low tail latency under high request volume.
Smooth connection handling across Envoy-Gunicorn boundaries.
Resilience to transient network blips.
This layer keeps the HTTP interface thin and efficient, just enough to route requests and parse payloads.
Core Serving Library
This is where the real logic lives. The LyftLearn Serving library handles the heavy lifting:
Model loading and unloading: Dynamically brings models into memory from saved artifacts
Versioning: Tracks and manages different model versions cleanly
Shadowing: Enables safe testing by running inference on new models in parallel, without affecting live results
Monitoring and logging: Emits structured logs, metrics, and tracing for each inference request
Prediction logging: Captures outputs for later audit, analytics, or model debugging
This library is the common runtime used across all teams. It centralizes the “platform contract” so individual teams don’t need to re-implement the basics. But it doesn’t restrict customization.
Custom ML/Predict Code
The core library is dependency-injected with team-owned inference logic. Every team provides two Python functions:
def load(self, file: str) -> Any: # Custom deserialization logic for the trained model ... def predict(self, features: Any) -> Any: # Custom inference logic using the loaded model ...Source: Lyft Engineering Blog
This design keeps the platform flexible. A team can use any model structure, feature format, or business logic, as long as it adheres to the basic interface. This works because the predicted path is decoupled from the transport and orchestration layers.
Third-Party ML Library Support
LyftLearn Serving makes no assumptions about the ML framework. Whether the model uses TensorFlow, PyTorch, LightGBM, XGBoost, or a home-grown solution, it doesn’t matter.
As long as the model loads and predicts through Python, it’s compatible. This lets teams:
Upgrade to newer framework versions without coordination.
Use niche or experimental libraries.
Avoid vendor lock-in or rigid SDKs.
Framework choice becomes a modeler’s decision, not a platform constraint.
Integration with Lyft Infrastructure
The microservice integrates deeply with Lyft’s existing production stack:
Metrics and tracing plug into the company-wide observability pipeline.
Logs and prediction events feed into central analytics systems.
Kubernetes handles service orchestration and autoscaling.
Envoy service mesh provides secure, discoverable network communication.
This alignment avoids duplicating effort. Teams inherit baseline reliability, visibility, and security from the rest of Lyft’s infrastructure, without needing to configure it themselves.
Isolation and Ownership Principles
When dozens of teams deploy and serve ML models independently, shared infrastructure quickly becomes shared pain. One broken deploy can block five others. A single library upgrade triggers weeks of coordination and debugging turns into blame-shifting. That’s what LyftLearn Serving was built to avoid.
The foundation of its design is hard isolation by repository, not as a policy, but as a technical boundary enforced at every layer of the stack.
One Repo, One Service, One Owner
Every team using LyftLearn Serving gets its own GitHub repository. This repo isn’t just for code, but it defines the entire model-serving lifecycle:
The service code includes custom load() and predict() logic.
The configuration files for deployment and orchestration.
The integration hooks for CI/CD, monitoring, and metrics.
There’s no central repository to manage and no shared runtime to coordinate. If a team needs five models, they can choose to host them in one repo or split them across five.
Independent Deploy Pipelines
Each repo comes with its deploy pipeline, fully decoupled from others. This includes:
Staging and production environments.
CI jobs that run model self-tests and linting.
Version tagging and release promotion.
If one team pushes broken code, it doesn’t affect anyone else. If another needs to hotfix a bug, they can deploy instantly. Isolation removes the need for cross-team coordination during high-stakes production changes.
Runtime Isolation via Kubernetes and Envoy
LyftLearn Serving runs on top of Lyft’s Kubernetes and Envoy infrastructure. The platform assigns each team:
A dedicated namespace in the Envoy service mesh
Isolated Kubernetes resources (pods, services, config maps)
Customizable CPU, memory, and replica settings
Team-specific autoscaling and alerting configs
This ensures that runtime faults, whether it’s a memory leaks, high CPU usage, or bad deployment. A surge in traffic to one team’s model won’t starve resources for another. A crash in one container doesn’t bring down the serving infrastructure.
Tooling: Config Generator
Getting a model into production shouldn’t mean learning multiple configuration formats, wiring up runtime secrets, or debugging broken deploys caused by missing database entries.
To streamline this, LyftLearn Serving includes a Config Generator: a bootstrapping tool that wires up everything needed to go from zero to a working ML serving microservice. Spinning up a new LyftLearn Serving instance involves stitching together pieces from across the infrastructure stack:
Terraform for provisioning cloud infrastructure.
YAML and Salt for Kubernetes and service mesh configuration.
Python is used for defining the serving interface.
Runtime secrets for secure credential access.
Database entries for model versioning or feature lookups.
Envoy mesh registration for service discovery.
Expecting every ML team to hand-craft this setup would be a recipe for drift, duplication, and onboarding delays. The config generator collapses that complexity into a few guided inputs.
The generator runs on Yeoman, a scaffolding framework commonly used for bootstrapping web projects, but customized here for Lyft’s internal systems.
A new team running the generator walks through a short interactive session:
Define the team name.
Specify the service namespace.
Choose optional integrations (for example, logging pipelines and model shadowing).
The tool then emits a fully-formed GitHub repo with:
Working example code for the load() and predict() functions.
Pre-wired deployment scripts and infrastructure configs.
Built-in test data scaffolds and CI setup.
Hooks into monitoring and observability.
Once the repo is generated and the code is committed, the team gets a functioning microservice, ready to accept models, run inference, and serve real traffic inside Lyft’s mesh. Teams can iterate on the model logic immediately, without first untangling infrastructure.
Model Self-Testing System
Model serving can often drift when a new dependency sneaks in, slightly changing output behavior. For example, a training script gets updated, but no one notices the prediction shift. Or, a container upgrade silently breaks deserialization. By the time someone spots the drop in performance, millions of bad inferences have already shipped.
To fight this, LyftLearn Serving introduces a built-in Model Self-Testing System. It’s a contract embedded inside the model itself, designed to verify behavior at the two points that matter most: before merge and after deploy.
Every model class defines a test_data property: structured sample inputs with expected outputs:
class SampleModel(TrainableModel): @property def test_data(self) -> pd.DataFrame: return pd.DataFrame([ [[1, 0, 0], 1], # Input should predict close to 1 [[1, 1, 0], 1] ], columns=["input", "score"])Source: Lyft Engineering Blog
This isn’t a full dataset. It’s a minimal set of hand-picked examples that act as canaries. If a change breaks expected behavior on these inputs, something deeper is likely wrong. The test data travels with the model binary and becomes part of the serving lifecycle.
Two checkpoints that matter are as follows:
During Deployment Runtime
After a model loads inside a LyftLearn Serving instance, it immediately runs predictions on its test_data. The results:
Get logged and surfaced in metrics dashboards.
Trigger alerts if predictions drift too far from expected.
Provide an immediate signal of runtime integrity.
This catches subtle breakages caused by environment mismatches. For example, a model trained in Python 3.8 but deployed into a Python 3.10 container with incompatible dependencies.
During Pull Requests
When a developer opens a PR in the model repo, CI kicks in. It performs the following activities:
Loads the new model artifacts.
Runs predictions on the stored test_data.
Compares outputs against previously known-good results.
If the outputs shift beyond an acceptable delta, the PR fails, even if the code compiles and the service builds cleanly. The diagram below shows a typical development flow:
Inference Request Lifecycle
A real-time inference system lives in the milliseconds between an HTTP request and a JSON response. That tiny window holds a lot more than model math. It’s where routing, validation, prediction, logging, and monitoring converge.
LyftLearn Serving keeps the inference path slim but structured. Every request follows a predictable, hardened lifecycle that allows flexibility without sacrificing control.
Here’s a step-by-step on how the request gets served:
Request hits the Flask endpoint: The service exposes an /infer route via Flask, backed by Gunicorn workers. Envoy handles the upstream routing. The incoming payload is parsed and handed off to the core serving library.
The core library retrieves the model: Using the model_id, the runtime looks up the corresponding model. If the model isn’t already loaded into memory, the system calls the team-supplied load() function and loads it on demand. This is where versioning logic, caching, and model lifecycle controls kick in. There’s no global registry and no shared memory. Each service owns and manages its models.
Input validation and preprocessing: Before running inference, the platform performs sanity checks on the features object, such as type or shape validation, required field presence, and optional model-specific hooks. This step guards against malformed inputs and prevents undefined behavior in downstream logic.
User-defined predict() runs the inference: Once the inputs are deemed valid, the system hands control to the custom predict() function written by the modeler. This function converts inputs into the expected format and calls the underlying ML framework (for example, LightGBM, TensorFlow) to return the prediction output. The predict() function is hot-path code. It runs millions of times per day. Its performance and correctness directly affect latency and downstream decisions.
Logs, metrics, and analytics: After the output is generated, the platform automatically logs the request and response for debugging and audit trails. It also emits latency, throughput, and error rate metrics and triggers analytics events that flow into dashboards or real-time monitoring. This observability layer ensures every inference can be traced and every service behavior can be measured.
Response returned to the caller: Finally, the result is packaged into a JSON response and returned via Flask. From request to response, the entire path is optimized for speed, traceability, and safety.
Conclusion
Serving machine learning models in real time isn’t just about throughput or latency. It’s about creating systems that teams can trust, evolve, and debug without friction.
LyftLearn Serving didn’t emerge from a clean slate or greenfield design. It was built under pressure to scale, to isolate, and to keep dozens of teams moving fast without stepping on each other’s toes.
Several lessons surfaced along the way, and they’re worth understanding:
“Model” means different things to different people. A serialized object, a training script, and a prediction endpoint all fall under the same label. Without clear definitions across tooling and teams, confusion spreads fast.
Documentation is part of the product. If teams can’t onboard, debug, or extend without asking the platform team, the system doesn’t scale. LyftLearn Serving treats docs as first-class citizens.
Once a model is deployed behind an API, someone, somewhere, will keep calling it. Therefore, stability is a requirement for any serving system that expects to live in production.
Trade-offs aren’t optional. Seamless UX conflicts with flexible composability. Structured pipelines clash with custom workflows. Every decision makes something easier and something else harder. The trick is knowing who the system is really for and being honest about what’s being optimized.
Power users shape the platform. Build for the most advanced, most demanding teams first. If the platform meets their needs, it’ll likely meet everyone else's. If not, it won’t scale past the first few adopters.
Prefer boring tech when it works. Stability, debuggability, and operational maturity are key aspects to consider.
LyftLearn Serving is still evolving, but its foundations hold. It doesn’t try to hide complexity, but it isolates it. Also, it enforces a contract around how the models behave in production.
References:
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by "ByteByteGo" <bytebytego@substack.com> - 11:38 - 10 Jun 2025 -
New: The smartest way to run HR and payroll
New: The smartest way to run HR and payroll
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Hi MD,
Growing your team shouldn’t mean juggling different tools for every country and every employee type. But for most companies, that’s the reality: up to 73% of time is lost to manual work, while payroll errors cost thousands.
Introducing Remote HRIS:
Effortless HR. Accurate payroll. All in one place.Remote HRIS brings all your employee data into one place, from hiring and onboarding to leave and time off, expenses, payroll, and more. You can:
- Hire and onboard employees and contractors anywhere
- Run payroll and HR in the same system
- Automate manual tasks with AI and no-code workflows
- Launch performance reviews with the new Remote Perform: a better way to manage feedback, goals, and reviews
And we're just getting started. Coming soon:
- A smarter way to manage compensation
- Automated onboarding workflows
- AI-powered engagement surveys
- ...and much, much more
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by "Remote Team" <hello@remote-comms.com> - 09:21 - 10 Jun 2025 -
Test our US ZIP code data - No signup required
Test our US ZIP code data - No signup required
👋 Hi there! In this edition of The Geodata Insider, I'm excited to share a new way you can explore our ZIP code and city data in the US.
2:30 minute read
📮 Explore our ZIP code data—no signup needed
📈 Master address validation across any platform
🛠️ Multi-language feature enhancement
🔎 Monthly changes
🌊 A sea adrift: Beautiful and borderless
Explore our US ZIP code data—no signup needed
Search any US ZIP code. Get the states, cities, population, accurate coordinates, and standardized formatting. It’s the same data that powers operations at Amazon, MercuryGate, and DB Schenker across 247 countries.
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Master address validation across any platform
Ready to eliminate address errors and boost data quality? Here is a list of step-by-step guides to ensure streamlined address validation.
Don't see your platform? Reply to this email with the system you're missing.
Smarter Language selection
Selecting the right language for users in multilingual countries like Canada and Switzerland has always been challenging.
GeoPostcodes multi-language data exports now include intelligent language recommendations by location, identifying the locally preferred language(s) for each area.
This ensures you always use the most appropriate language for your users' locations, improving data accuracy and user experience.
Monthly changes
Full Postal & Street updates
Australia, Netherlands
Postal database patches
(small changes)
Argentina (Postcodes),
Croatia (Postcodes), Italy (Postcodes), Philippines (Administrative divisions)
Postal boundary patches (small changes)
China, Spain
Administrative boundaries patches (small changes)
Denmark
For a detailed changelog, take a look at the CSV file.
A sea adrift: Beautiful and borderless
Forget everything you know about oceans—there’s one sea that plays by none of the rules. The Sargasso Sea doesn’t touch a single shore. No beaches, no cliffs, no coastline.
Instead, it floats in the middle of the Atlantic, held together by four swirling currents.
Inside this watery loop, a golden jungle of Sargassum seaweed drifts on the surface.
It’s a nursery for turtles, an eel breeding ground, and a pit stop for whales and tuna.The Sargasso is now home to the North Atlantic Garbage Patch: thousands of plastic pieces per square kilometre.
A place that exists without borders… and reminds us what happens when we cross them. Follow us on LinkedIn for more geographical facts like this!
Kind regards,
Jerome & the GeoPostcodes team
PS: Interested in previous Monthly Product Updates? Read here.
GeoPostcodes, Bld Bischoffsheim 15, 1000 Bruxelles, Belgium
by "Jérôme from GeoPostcodes" <jerome@geopostcodes.com> - 06:35 - 10 Jun 2025 -
Excelling as a leader: Decision making
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Faster, better decisions
In the previous session, we explored the mindsets and behaviors of growth leaders. In this second email, we'll explore how to cultivate careful—yet bold—decision making. Today’s leaders are faced with hard choices and more pressure than ever. Here are some ways to set yourself up for more successful decisions.
Executives today spend about 40 percent of their time making decisions—and 60 percent say that time is poorly used. The opportunity costs of these inefficiencies are hard to reconcile: for the typical Fortune 500 company, about 530,000 days of managers’ time is potentially squandered each year. That’s equivalent to around $250 million in wages annually.
Much of this time is spent in meetings, says McKinsey senior partner Aaron De Smet. But “most meetings are designed to not make a decision,” he says. So the inefficiency perpetuates itself.
It doesn’t have to be this way. Check out these insights to cultivate your skill as a decision maker under any circumstances.
This email contains information about McKinsey’s research, insights, services, or events. By opening our emails or clicking on links, you agree to our use of cookies and web tracking technology. For more information on how we use and protect your information, please review our privacy policy.
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by "McKinsey Publishing Guides" <publishing@email.mckinsey.com> - 03:17 - 10 Jun 2025 -
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by "Samantha - VIP Golf Concierge" <info@vipgolfbookings.co.uk> - 03:02 - 10 Jun 2025 -
What are the fashion industry’s biggest themes in 2025?
On McKinsey Perspectives
Brought to you by Alex Panas, global leader of industries, & Axel Karlsson, global leader of functional practices and growth platforms
Welcome to the latest edition of Only McKinsey Perspectives. We hope you find our insights useful. Let us know what you think at Alex_Panas@McKinsey.com and Axel_Karlsson@McKinsey.com.
—Alex and Axel
•
Fashion’s 2025 outlook. Amid consumers’ unease, supply chain concerns, and shifts in global trade, the fashion industry is facing a challenging year. Despite these risks, McKinsey’s latest State of Fashion research reveals that there are still opportunities for brands to capture. That’s according to Senior Partner Gemma D’Auria, who discusses the research’s key findings in a recent episode of The McKinsey Podcast. Fashion leaders can help their businesses grow by using AI and AI-led tools to engage directly with customers and offer personalized shopping experiences, both online and in stores, D’Auria explains. McKinsey’s previous State of Fashion research found that up to 25% of AI’s potential in fashion can enhance the industry’s creative side.
—Edited by Belinda Yu, editor, Atlanta
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Copyright © 2025 | McKinsey & Company, 3 World Trade Center, 175 Greenwich Street, New York, NY 10007
by "Only McKinsey Perspectives" <publishing@email.mckinsey.com> - 01:28 - 10 Jun 2025 -
Register: Driving innovation with custom Joule skills and agents
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[3 PM ET | 3 PM CET | 3 PM SGT]AI tools are taking productivity to new levels. But why stop at out-of-the-box solutions?
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by "The SAP Build team" <sap@mailsap.com> - 12:20 - 10 Jun 2025 -
Grab your spot: Join our AI Readiness for SMBs webinar
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Let Us Handle Your Air Freight Needs with Care and Expertise From China To Mexico
Dear Mr/MsYou can throw coins into a fountain and wish for:Fast transit
Or...You can email us.We’re not magical, but we do answer. Fast. And honestly.From China to Mexico ― no wishes needed.
Pls kindly find the following the Air rate for general cargo for FOB:ASLG FOB Rate - Week24 2025 AIR EXPORT Airline station Route Weight breaks FRQ T/T Remark Carrier Org Dest 100+ 300+ 500+ 1000+ HU PEK MEX PEK-MEX $4.65 $4.65 $4.65 $4.65 Daily Direct 1cbm>300kgs stackable BA/AF PEK MEX PEK-LHR/CDG-MEX $5.05 $5.05 $5.05 $4.95 Daily 4-5Days 1cbm>300kgs stackable NH PEK MEX PEK-NRT-MEX $5.05 $5.05 $5.05 $4.95 Daily 2-3Days 1cbm>300kgs stackable CZ PVG NLU PVG-NLU $5.35 $5.35 $5.35 $5.35 D1356 Direct 1cbm>300kgs stackable K4 CGO NLU CGO-NLU $5.35 $5.35 $5.35 $5.35 D246 Direct 1cbm>300kgs stackable 5Y PVG GDL PVG-GDL $5.50 $5.50 $5.50 $5.50 D3 Direct 1cbm>300kgs stackable 5Y XMN NLU XMN-NLU $5.35 $5.35 $5.35 $5.35 D247 Direct 1cbm>300kgs stackable CA/CZ SZX MEX SZX-MEX $4.85 $4.85 $4.85 $4.85 D246 Direct 1cbm>300kgs stackable 5Y HKG NLU/GDL HKG-NLU/GDL $6.20 $6.20 $6.20 $6.20 TBA Direct Battery cargo CX HKG NLU/GDL HKG-NLU/GDL $6.20 $6.20 $6.20 $6.20 D24567 Direct Battery cargo CV HKG NLU/GDL HKG-NLU/GDL $6.20 $6.20 $6.20 $6.20 D1235 Direct Battery cargo Pls noted that you have ready cargo,I will check the special air rate for case by case.Hope the above is helpful for you,if any progress,pls feel free to let me know in time.
Best Regards
Vic Yang
Overseas Departments | Airsupply Logistics Limited
**Focus on international air cargo service, welcome for checking with me any time.**A: Floor 23th Bldg 13 South Park Baoneng Science and Technology Industrial Park,No.1 Qingxiang Road,Longgang Shenzhen,China
B: SZX/CAN/HKG/CSX/PVG/TSN/PEK
WCA ID: 104615 RA:28426 NVOCC: 09626
发件人： vic07@air-supply.biz发送时间： 2025-02-19 12:23收件人： info主题： Let Us Handle Your Air Freight Needs with Care and Expertise From China To MexicoDear Mr./Ms.
We know life’s busy―so when you need to move your goods from China To Mexico, you want it fast, secure, great service and great rate.
Well, guess what? We’ve got your back!
Pls kindy find the following the Air rate for general cargo for FOB:ASLG FOB Rate - Week8 2025 AIR EXPORT Airline station Route Weight breaks FRQ T/T Remark Carrier Org Dest 100+ 300+ 500+ 1000+ HU PEK MEX PEK-MEX $3.06 $3.06 $2.72 $2.72 Daily Direct 1cbm>300kgs stackable BA/AF PEK MEX PEK-LHR/CDG-MEX $3.06 $3.06 $2.72 $2.72 Daily 4-5Days 1cbm>300kgs stackable NH PEK MEX PEK-NRT-MEX $3.06 $3.06 $2.72 $2.72 Daily 2-3Days 1cbm>300kgs stackable CZ PVG NLU PVG-NLU $4.00 $4.00 $4.00 $4.00 D146 Direct 1cbm>300kgs stackable K4 CGO NLU CGO-NLU / / / / D246 Direct 1cbm>300kgs stackable 5Y PVG GDL PVG-GDL $4.00 $4.00 $4.00 $4.00 D3 Direct 1cbm>300kgs stackable 5Y XMN NLU XMN-NLU / / / / D247 Direct 1cbm>300kgs stackable CA/CZ SZX NLU SZX-NLU $3.00 $3.00 $2.85 $2.85 D246 Direct 1cbm>300kgs stackable 5Y HKG NLU/GDL HKG-NLU/GDL $6.10 $6.10 $6.10 $6.10 TBA Direct Battery cargo CX HKG NLU/GDL HKG-NLU/GDL $6.10 $6.10 $6.10 $6.10 D24567 Direct Battery cargo CV HKG NLU/GDL HKG-NLU/GDL $6.10 $6.10 $6.10 $6.10 D1235 Direct Battery cargo
Pls noted that you have ready cargo,I will check the special air rate for case by case.Hope the above is helpful for you,if any progress,pls feel free to let me know.We are eager to explore potential collaboration and support your logistics requirements. Pls don’t hesitate to reach out for more details.
Best Regards
Vic Yang
Overseas Departments | Airsupply Logistics Limited
**Focus on international air cargo service, welcome for checking with me any time.**A: Floor 23th Bldg 13 South Park Baoneng Science and Technology Industrial Park,No.1 Qingxiang Road,Longgang Shenzhen,China
B: SZX/CAN/HKG/CSX/PVG/TSN/PEK
WCA ID: 104615 RA:28426 NVOCC: 09626
发件人： vic07@air-supply.biz发送时间： 2025-01-02 17:22收件人： info主题： Let Us Handle Your Air Freight Needs with Care and Expertise From China To MexicoDear Mr./Ms.
Happy New Year on 2025!!!Imagine this: Your critical cargo glides effortlessly from China’s busiest airports and lands precisely on schedule, handled with precision and care every step of the way, and efficient transportation with airlines.
My name is Vic from Airsupply, where we specialize in providing expert logistics solutions tailored to the needs of international trade.At Airsupply, we make this vision a reality, Here’s how we roll out the red carpet for your shipments:
Our Services:
- Extensive Network: Direct/Transfer routes from major Chinese airports (HKG/SZX/CAN/PVG/PEK/CGO) to MX/US/CA and Latin America, partnering with leading carriers (CZ/CA/HU/NH/OZ/K4/5Y/FX/CX/CV etc...).
- Global Certifications: IATA-certified, JCtrans Golden Member, WCA-approved.
- Strategic Expertise: Master loader at HKG Airport with exclusive airline advantages (CX/CV/5Y/FX/M7/OZ/KE/LO etc...).
- DG Cargo Handling: Safe and compliant transport of hazardous materials (Class 2/3/4/5/6/8/9) with IATA DGR approval.
- Integrated Logistics: Inland trucking, door-to-door DDU/DDP delivery, and seamless customs clearance for air and sea shipments.
- Value-Added Services: Cargo insurance, charter services, project cargo handling, custom brokerage, and trade show logistics expertise.
At the same time, we also need your company to provide us with the following services:
- Air/Sea Freight:Efficient transport from your country to China or other global ports.
- Inland Trucking/Delivery: Including DDU&DDP for door-to-door services.
- Customs Clearance:Seamless import and export customs clearance for both Air&Sea.
We look forward to exploring collaboration opportunities and supporting your logistics needs. Please feel free to contact me for more information.
Thank you for considering Airsupply. We hope to contribute to your global success.
If you need to learn more about us, please watch our YouTube video:https://youtu.be/euPxeTaVxv0
When you do not desire to receive future emails from us,pls let us know in time, and we will remove you from our mailing list. Thanks.
Best Regards
Vic Yang
Overseas Departments | Airsupply Logistics Limited
**Focus on international air cargo service, welcome for checking with me any time.**A: Floor 23th Bldg 13 South Park Baoneng Science and Technology Industrial Park,No.1 Qingxiang Road,Longgang Shenzhen,China
B: SZX/CAN/HKG/CSX/PVG/TSN/PEK
WCA ID: 104615 RA:28426 NVOCC: 09626
by "vic07@air-supply.biz" <vic07@air-supply.biz> - 11:26 - 9 Jun 2025 -
Introduction to Precision Metal Processing Solutions from Zhuolida
Dear Info,
This's Zhuolida-etching,sales manager from Zhuolida, We are one of the biggest Metal processing manufactures in China.
I got to know that you are interested in an Precision Metal Parts, our company has an extensive experience on
such kind of automotive spring plates, gaskets, and automotive oil filter mesh.
We have precision metal etching, precision electroforming, laser cutting, surface plating multi-combination process,
is China's largest multi-process combination of metal parts processing manufacturer.
We have worked for a long time with customers like Kyocera and Auto Toyotafor such products.
Best Regards
Zhuolida-etching
Project Manager
Shenzhen Zhuolida Electronics Co.,Ltd.
WhatsApp:+8618938693450/+860755-27088292
Add: Building A3, Huafa Industrial Park, Fuyong Town, Fuyuan Road, Fuyong Town, Baoan District, Shenzhen，China.
by "zhuolida-etching" <zhuolida-etching@zld-waimao.com> - 08:25 - 9 Jun 2025 -
High-Quality Quartz Products for Your Business Needs
Dear Info，
I hope you’re doing well. I’m [karensun], and I represent [SouthEast Quartz ], a leading manufacturer specializing in high-quality quartz products.
We offer a wide range of products including quartz sheets, tubes, crucibles, glass tubes, slides, boats, rods, and more, used across industries such as semiconductor, solar energy, chemicals, medical devices, and scientific instruments. Our products are well-regarded for their purity, durability, and performance.
With advanced technology, strict quality control, and a strong reputation in both domestic and international markets, we serve clients in over 20 provinces in China and export to regions like Korea, Southeast Asia, Europe, and the Americas.
If you’re interested in discussing how our quartz products can meet your needs, please feel free to reach out. We look forward to the opportunity to work with you.
Thanks and best regards
karensun
SouthEast Quartz Products Co., Ltd
Mob：+86-135 8528 6180
Email: karen.sun@dnquartz.com
Website：www.dnquartz.com
by "Mamaclay Kalua" <mamaclaykalua49@gmail.com> - 07:47 - 9 Jun 2025 -
¡Tu equipo esta invitado a una clase gratuita de ventas!
Hola, buen día:
Fue un gusto platicar con tu equipo que muy amablemente me compartió este correo porque vio que podría aportar mucho para su empresa, les agradezco mucho la apertura.
Me permito escribirte porque estoy convencido de que lo que hacemos puede aportar muchísimo valor al área comercial de la empresa.Seré breve:
Me gustaría coordinar una demo gratuita, una clase virtual en vivo de unos 25 minutos, pensada para equipos comerciales que quieren mejorar su tasa de cierres con técnicas prácticas y de impacto inmediato.Durante esta sesión, además de mostrar lo que hacemos, los participantes se llevan ideas que pueden aplicar desde el primer día. No es una presentación de ventas, es una experiencia real de lo que brindamos.
Entendí que no estaba en sus manos el tomar esta decisión, agradecería mucho si pudieras ayudarme a canalizar esta propuesta con la persona adecuada (tal vez el responsable del área comercial o quien lidere al equipo de ventas).
Te dejo aquí un enlace con más información y algunos casos reales de empresas con las que ya estamos colaborando:
Sitio web: https://factorstudios.io/
Pagina de historias de éxito: https://www.campamentodeventa.com/casos-de-exito
Instagram César (CEO del área de capacitaciones corporativas): https://www.instagram.com/cesarjorqueraq/
Instagram Tino (Fundador de la universidad del closer): https://www.instagram.com/tino.mossu/
Instagram de Teo (Fundador del área de implementación de vendedores en empresas):
https://www.instagram.com/teotinivelli/
by "FactorStudios" <ventasfactorstudios@gmail.com> - 02:12 - 9 Jun 2025 -
Our New Book, Mobile System Design Interview, Is Now Available
Our New Book, Mobile System Design Interview, Is Now Available
Forwarded this email? Subscribe here for moreOur new book, Mobile System Design Interview, is available on Amazon!
Book author: Manuel Vicente Vivo
𝐖𝐡𝐚𝐭’𝐬 𝐢𝐧𝐬𝐢𝐝𝐞?
- An insider's take on what interviewers really look for and why.
- A 5-step framework for solving any mobile system design interview question.
- 7 real mobile system design interview questions with detailed solutions.
- 24 deep dives into complex technical concepts and implementation strategies.
- 175 topics covering the full spectrum of mobile system design principles.
𝐓𝐚𝐛𝐥𝐞 𝐎𝐟 𝐂𝐨𝐧𝐭𝐞𝐧𝐭𝐬
Chapter 1: Introduction
Chapter 2: A Framework for Mobile System Design Interviews
Chapter 3: Design a News Feed App
Chapter 4: Design a Chat App
Chapter 5: Design a Stock Trading App
Chapter 6: Design a Pagination Library
Chapter 7: Design a Hotel Reservation App
Chapter 8: Design the Google Drive App
Chapter 9: Design the YouTube app
Chapter 10: Mobile System Design Building Blocks
Quick Reference Cheat Sheet for MSD Interview
If you have any questions, please leave a comment.
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