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Palletizing frosting buckets with Robotiq + Alba

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When your product is frosting and your purpose is to maneuver it—quick, clear, and with out breaking a sweat—you don’t need to depart something to likelihood. That’s precisely why one bakery producer teamed up with Robotiq and Alba to automate their bucket palletizing course of. The mission? Stack a wide range of frosting bucket sizes onto CHEP and GMA pallets with out guide labor or downtime.

Spoiler alert: mission completed.

Be taught Greenhouse Gasoline Accounting for IT with Cisco Networking Academy


Greenhouse fuel (GHG) accounting is changing into important throughout each business. Nevertheless, IT has typically been unnoticed of the dialog. That’s why local weather schooling chief One Level 5 Academy has partnered with Cisco Networking Academy to create the “Introduction to Greenhouse Gasoline Accounting for IT” course. This free course helps IT professionals purchase the talents to measure, report, and cut back emissions related to knowledge facilities, cloud infrastructure, and computing {hardware}—guaranteeing IT groups are geared up to assist their organizations’ sustainability objectives.

What’s within the “Introduction to Greenhouse Gasoline Accounting for IT” course?

One Level 5 Academy makes a speciality of serving to learners break into inexperienced careers, whereas Cisco Networking Academy focuses on getting ready learners for the IT area, making them a robust mixture. This entry-level course attracts from OnePointFive Academy’s complete eight-week sustainability expertise accelerator program and takes simply two to 3 hours whole.

It’s accessible as both self-paced or instructor-led and can be utilized as a standalone workshop or as supplemental studying, and contains:

  • 1 hour of video classes
  • 1.5 hours of interactive lab work
  • Teacher-led coaching accessible
  • Earn a digital Credly badge, shareable on LinkedIn

The course teaches you:

  • The fundamentals of GHG accounting
  • What Scope 1, 2, and three emissions are, and find out how to distinguish between them
  • The right way to conduct fundamental greenhouse fuel calculations
  • IT-specific emissions discount methods
  • Sustainability reporting and compliance necessities
  • An IT-specific case examine on an IT {hardware} producer

Who’s Introduction to Greenhouse Gasoline Accounting for IT for?

This brief course is good for:
• IT professionals seeking to construct inexperienced expertise
• Sustainability professionals attempting to know tech emissions
• Faculty and vocational college students in IT, enterprise, or environmental science
• Profession changers transitioning into ESG and climate-related roles

Do I must know something about GHG accounting?

No prior data of GHG accounting is required—simply curiosity and curiosity within the intersection of IT and sustainability.

Which jobs are GHG accounting-related?

This course aligns with a rising set of sustainability-related job roles, together with:
• ESG Information Analyst
• IT Operations Supervisor with a sustainability lens
• Know-how Advisor (local weather or ESG focus)
• Information Middle Sustainability Specialist

Is “Introduction to Greenhouse Gasoline Accounting for IT” tied to a Cisco certification?

Whereas Introduction to Greenhouse Gasoline Accounting for IT isn’t tied to a proper Cisco certification, it does offer you a validated Credly badge to show to employers you’ve discovered invaluable data and lays a powerful basis for additional examine.

This course additionally serves as an amazing launchpad for Networking Academy’s broader IT curriculum. Programs like Networking Fundamentals and Cybersecurity Necessities are pure subsequent steps when you earn your Credly badge.

Begin studying totally free at the moment

You will get began with the self-paced model of Introduction to Greenhouse Gasoline Accounting for IT at the moment or find an in-person, instructor-led course close to you.

What do you concentrate on IT’s function in sustainability? Do you see a niche in GHG Accounting for IT schooling? Tell us your ideas within the feedback.

 

A Extra Sustainable Future for Africa: Cisco’s Position in Bridging the Digital Divide

 

 

 

 

 

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Overland AI demonstrates full-stack floor autonomy for uncrewed breaching

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Overland AI demonstrates full-stack floor autonomy for uncrewed breaching

Overland AI built-in its OverDrive software program stack and SPARK {hardware} into the Normal Dynamics Small Multipurpose Gear Transport. | Supply: Overland AI

Overland AI yesterday mentioned it has efficiently demonstrated its autonomous floor automobile built-in with its uncrewed aerial system, or UAS-capable payloads as a part of a joint breaching experimentation effort with the Sandhills Challenge and the twentieth Engineer Brigade of the XVIII Airborne Corps.

The Seattle-based firm accomplished the demonstration on the U.S. Military’s premier expertise innovation occasion, Challenge Convergence Capstone 5 (PC-C5).

Based in 2022, Overland AI mentioned it’s powering floor operations for contemporary protection. The corporate has performed greater than a decade of superior analysis in robotics and machine studying. That and its field-test ahead ethos enable it to ship superior autonomy for unit commanders.

Overland AI mentioned developed OverWatch, its intuitive C2 interface, to supply commanders with the exact coordination of autonomous floor techniques wanted for advanced missions to succeed. The corporate claimed that it has achieved the end-to-end integration of floor autonomy, from operator to impact. It mentioned it’s placing this functionality into the fingers of tactical operators at this time.

SMET autos achieve autonomy

Hazardous missions in austere and electronically denied environments require dependable and resilient expertise, famous Overland AI. It mentioned its SPARK autonomy upfit and OverDrive stack allow floor autos to navigate off-road with out GPS or direct operator management.

The corporate constructed its totally autonomous tactical automobile, ULTRA, in-house by integrating SPARK and OverDrive right into a modular and adaptable platform that’s presently in manufacturing. The U.S. navy is testing a number of ULTRA autos, which might carry 1,000 lb. (453.5 kg), transfer as much as 35 mph (56.3 kph), and cruise for 100 mi. (160.9 km).

Working underneath the course of the Sandhills Challenge, Overland AI built-in its full stack of autonomy {hardware} and software program into Normal Dynamics Land Methods’ Small Multipurpose Gear Transport (SMET) automobile. The expertise has additionally been built-in with the Textron Ripsaw and Polaris RZR.

The SMET was initially managed by way of a tethered hand distant. Now, Overland AI’s OverDrive software program stack, SPARK {hardware} infrastructure, and OverWatch tactical interface allow autonomous operation.

Overland AI reveals help of Sandhill Challenge targets

U.S. Military troopers from the twenty seventh Engineer Battalion, twentieth Engineer Brigade, skilled instantly on Overland’s system throughout PC-C5. The troopers realized to independently function, troubleshoot, and keep the totally autonomous platform.

By the top of the train, they executed breaching missions, efficiently beginning up the Autonomous Floor System, conducting missions, and shutting it down independently.

The demonstration included two payload integrations. The primary was a trailer geared up with a mine-clearing UAS designed for breaching a lane. Within the second, a Stratin Engineering-developed drone launcher mounted on the SMET to deploy small attritable drones.

“Troopers independently and efficiently operated our floor autonomy for 2 consecutive weeks throughout Challenge Convergence Capstone 5,” said Byron Boots, co-founder and CEO of Overland AI. “Breaching workouts proceed to display the maturity of {our capability} and the tactical advantage of eradicating people from a number of the most harmful missions.”

Overland AI instantly supported the Sandhills Challenge’s goal, corresponding to minefields, wire, and ditches, whereas enabling distributed operations throughout a breach. The twentieth Engineer Brigade now has the upgraded SMET automobile for continued testing, and Overland AI will present discipline help and a software program license underneath its contract.

PC-C5 is a key a part of the Military’s persistent analysis and testing of next-generation warfighting capabilities, together with cross-domain operations within the INDOPACOM (Indo-Pacific) theater. The Overland AI floor workforce a the train included specialists throughout {hardware} integration, autonomy software program, infrastructure, discipline operations, product, and program administration.

Overland AI mentioned it continues to advance the state of floor autonomy for protection, having beforehand secured an $18.6 million contract with the U.S. Military and Protection Innovation Unit (DIU) to develop autonomy software program for the Robotic Fight Car (RCV) program.


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Scalable ML & Information Testing


In as we speak’s digital platforms-from purchasing apps and streaming companies to well being trackers and buyer portals-machine studying is central to how methods personalize experiences, automate selections, and reply to person actions. However irrespective of how superior a mannequin is, it may possibly fail if the info feeding it isn’t dependable.

Creator: Naga Harini Kodey, https://www.linkedin.com/in/naga-harini-k-3a84291a/

With fixed streams of person interactions-clicks, swipes, logins, transactions, and events-flowing by way of these methods, sustaining information accuracy turns into a foundational requirement. Damaged information pipelines, inconsistent function values, and unmonitored modifications can result in silent failures. These failures typically go unnoticed till person satisfaction drops or key enterprise metrics take a success.

As a Principal QA Engineer, I’ve collaborated carefully with engineers, analysts, and information scientists to check machine studying pipelines end-to-end. This text outlines sensible QA methods and hands-on methods that may be utilized throughout platforms pushed by real-time or batch person information, serving to groups stop points earlier than they affect manufacturing.

The place Issues Go Fallacious in ML Pipelines for Consumer Programs

Consumer-driven platforms acquire information from a variety of sources-web exercise, cell apps, sensor inputs, and exterior APIs. As this information flows by way of ingestion, transformation, and mannequin scoring, there are a number of widespread failure factors:

  • Lacking fields in logs → Instance: System sort or session ID not logged constantly throughout cell and internet.
  • Inconsistent occasion naming → Instance: checkoutInitiated modified to checkout_initiated, breaking downstream dependencies.
  • Unrealistic or incorrect values → Instance: Session time reveals zero seconds or logs a person clicking 200 occasions in a second.
  • Code modifications with out validation → Instance: Characteristic transformation logic up to date with out verifying downstream mannequin compatibility.
  • Mismatch in coaching vs. manufacturing → Instance: Fashions educated on curated information however deployed on noisy, real-world inputs.
  • Check site visitors contaminating dwell information → Instance: Automated testing scripts inadvertently included in manufacturing metrics.
  • Damaged suggestions loops → Instance: Retraining logic relies on a sign that silently stops firing.

These issues typically degrade efficiency subtly-skewing suggestions or altering person flows-making them more durable to detect with out focused validation.

Scalable ML & Information Testing

Testing Methods That Work in Observe

Every stage of the pipeline-from uncooked occasion seize to function transformation to mannequin output-presents a novel testing alternative. Right here’s a breakdown of sensible methods:

1. Begin on the Supply: Uncooked Information Validation

Widespread points: Lacking timestamps, corrupted machine IDs, inconsistent information codecs.

How one can check it:

  • Construct schema validators utilizing instruments like Nice Expectations or Cerberus.
  • Set automated thresholds for lacking values (e.g., alert if >5% of user_id fields are null).
  • Monitor ingestion volumes over time; flag sudden drops/spikes in key occasions.

Instance Implementation:

python –

assert occasion[‘timestamp’] is just not None

assert isinstance(occasion[‘device_id’], str)

2. Confirm Characteristic Logic

Widespread points: Incorrect logic in options like session length, or loyalty rating.

How one can check it:

  • Write unit checks for transformation capabilities utilizing identified pattern inputs.
  • Outline worth bounds or anticipated distributions (e.g., session length shouldn’t be > 12 hours).
  • Embrace logging checkpoints to confirm computed values at every stage.

Guidelines Tip: Create a function contract doc itemizing every function, supply columns, transformation steps, and check circumstances.

3. Look ahead to Coaching vs. Manufacturing Drift

Widespread points: Characteristic values differ between coaching and manufacturing environments.

How one can check it:

  • Run statistical comparability (e.g., KS check or PSI) between offline coaching information and dwell enter information.
  • Add a nightly job to check means, medians, and ranges of energetic options.
  • Visualize function drift on dashboards to trace gradual degradation.

Alert Instance: “Characteristic X imply has shifted from 0.2 to 0.45 over the previous 7 days.”

4. Lock Down Enter and Output Expectations

Widespread points: Schema mismatches, renamed fields, or lacking inputs trigger the mannequin to misbehave.

How one can check it:

  • Use golden input-output pairs as regression circumstances in your CI pipelines.
  • Add an enter validation layer that enforces construction, information varieties, and presence of required fields.
  • Log and evaluate mannequin output distributions throughout variations.

Observe Tip: All the time pin a “canary” check with a identified document that ought to give a set prediction rating.

5. Monitor for Silent Failures

Widespread points: All the pieces runs, however person engagement or conversions drop unexpectedly.

How one can check it:

  • Construct dashboards for monitoring scoring quantity, function completeness, and mannequin predictions.
  • Cross-check enter function presence day by day and evaluate it with coaching schema.
  • Arrange anomaly detection on output KPIs (conversion price, engagement price).

Instance: “If purchase_probability output from the mannequin drops by 30% over 3 days, flag it for investigation.”

Finest Practices for Testing ML Pipelines

  • Check early, check small: Validate information earlier than it hits your transformation logic.
  • Create edge circumstances: Deliberately go invalid or boundary values to check mannequin resilience.
  • Monitor and model every part: Keep lineage for datasets, options, and scripts.
  • Automate regression checks: Each mannequin launch ought to be backed by automated state of affairs validation.
  • Collaborate throughout capabilities: QA, information science, product, and engineering ought to evaluation pipelines collectively.
  • Make failures seen: Spend money on real-time alerting and dashboards. Fewer surprises = higher outcomes.

Conclusion

For platforms pushed by person interplay, machine studying can’t succeed with out reliable information. When pipelines break silently, the affect hits person expertise, retention, and income. Testing these methods must be proactive, systematic, and tailor-made to real-world circumstances.

Scalable check protection ensures each component-from information ingestion to mannequin scoring-holds up beneath stress. By specializing in root-level information integrity and transformation validation, QA groups grow to be vital gatekeepers of efficiency and reliability.

Testing isn’t nearly catching bugs-it’s about safeguarding the intelligence behind your platform.

References / Additional Studying

Concerning the Creator

Naga Harini Kodey is a Principal QA Engineer with over 15 years of expertise in automation, information high quality, and machine studying validation. She focuses on testing AdTech information pipelines and ML workflows, builds check frameworks, and a worldwide speaker on QA methods, information testing and end-to-end machine studying system assurance.

How a Ardour for Languages Led to a International Profession at Cisco


“¿Qué ondas?”

That’s a well-recognized greeting in El Salvador, the place I’m from, a land the place surf and occasional mix harmoniously.Students in a classroom use laptops while an instructor in a blue shirt stands near a whiteboard with a diagram, in a room with large windows, a wooden floor, a blue checkmark in the top right, and a cloud icon in the bottom right.

Once I was rising up there as a child, my grandma requested me if I needed to take summer time courses. She gave me three decisions: drawing, math, or English courses. On the time, I felt like I used to be ok in math. I used to be extra into music than drawing. So, she paid for my summer time English courses. Little did I do know that her humble pension and that call would change my life ceaselessly.

After that first summer time English class, I developed a ardour for international languages, changing into fluent in French, Portuguese, and English, and studying some German, along with my native Spanish. I went to courses within the early mornings and labored into the late nights — this was my life for just a few years, finding out and dealing on the identical time. Weekends have been reserved for rehearsing with my rock band and educating English and French at an academy. Years later, I obtained my MBA in Logistics.

A group of five people in athletic wear, posing cheerfully outdoors after a race, wearing numbered bibs and smiling with thumbs up.I believed I used to be headed towards a way forward for educating, however after I was not chosen for a educating function, it led me to use for and get an engineer function with a Canadian firm, a Cisco accomplice. The humorous factor is that if that hadn’t occurred, I most likely wouldn’t be working at Cisco at the moment. I consider life has a method of providing you with what’s meant to be yours.

Somebody inside Cisco advised me a couple of French Consulting Engineer function at Cisco Poland, and whereas I used to be excited for the chance, shifting to Europe was a giant resolution. I had every thing at house — my household, associates, band — nevertheless it felt just like the time to problem myself, evolve, and fly. I nonetheless keep in mind taking part in Eminem’s “Lose Your self” earlier than my ultimate interview, understanding this could possibly be a once-in-a-lifetime alternative. Coming to work for Cisco meant the possibility to make an affect in a prime tech firm.

Once I first moved to Poland, I didn’t know many individuals, so I introduced a bit of little bit of house to Cisco, organizing soccer video games to have enjoyable and join with folks. It helped me, as a newcomer, combine by way of sport with the worldwide group. Since then, I’ve organized singing and occasional workshops and know-how occasions every time I can to construct bridges, join folks, and improve our office expertise. Even after three years,A person stands on a street in Paris, taking a photo of the Eiffel Tower on a cloudy day, surrounded by classic Parisian buildings. Cisco continues to amaze me with its tradition, inclusion, and all of the methods we will convey ourselves into our work.

I started at Cisco as a consulting engineer the place I labored in design, implementation, and consultancy of Cisco options. Over three unbelievable years, I’ve gained a variety of expertise, transitioned to safety, and am tremendous grateful to have acquired two promotions. I’m now a senior consulting engineer of safety and collaboration applied sciences the place I work with monetary establishments to offer community safety and videoconferencing.

This 12 months, I launched into a enterprise journey to France, aiding with videoconferencing deployment and design for a number one monetary establishment, and my life got here full circle in a method I by no means may have imagined. I’m nonetheless educating, however now sharing my data with prospects and colleagues on a worldwide scale. The general public talking abilities I honed singing and taking part in dwell with my band ready me for presenting options to executives on-site and interacting with them in these convention rooms in Paris. I by no means imagined that my ardour for languages would lead me to a profession in know-how, not to mention impactful moments like these at an organization like Cisco. And none of this might have been attainable with out my grandma and people summer time English courses. Visiting Paris made me understand how lucky I’m.

My profession path up to now has taught me that being open to alternatives, dedicating your self to lifelong studying, and being resilient to challenges are the keys to success. In the event you embrace this, I’ve little question you’ll not solely ‘make it,’ you’ll thrive, identical to I’ve at Cisco!

Are you able to thrive at Cisco? Study extra and discover alternatives now.

Subscribe to the WeAreCisco Weblog.

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