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Killexams : Nortel Engineeing test - BingNews Search results Killexams : Nortel Engineeing test - BingNews Killexams : Test Connections Clean Up With Real-Time Maintenance

Test facilities are beginning to implement real-time maintenance, rather than scheduled maintenance, to reduce manufacturing costs and boost product yield.

Adaptive cleaning of probe needles and test sockets can extend equipment lifetimes and reduce yield excursions. The same is true for load board repair, which is moving toward predictive maintenance. But this change is much more complicated than it might appear. It requires determining which parameters correlate directly with the need to clean, and in having sufficient fault coverage in the board diagnostic programs.

Probe cards and load boards provide the electrical interface between the device under test (DUT) and the ATE. Rising IC complexity and an increasing number of board pins contribute to an increasing cost and cost of ownership of these test boards. Timely maintenance extends board lifetime and improves equipment efficiency.

Until recently, maintenance activities were performed at fixed intervals, typically during ATE configuration changes or when a yield excursion indicates a potential board issue. Motivated by a reduction in total cost of ownership and increased yield, the industry is shifting to real-time or adaptive cleaning procedures and general board maintenance. In some cases teams are adding a machine vision capability to help detect issues.

Rising cost per board
Cost is the key driver for all of this. Test boards are becoming more expensive, and an increase in multi-site testing leads to a greater number of probes per wafer contact, or contacts per unit. So while more transistors per SoC increases the number of power pins and I/O pins required, the trends are similar for load board design in package test.

With preventive maintenance, engineers rely on maintenance schedules. Cleaning is typically performed after a set number of contacts, and board maintenance often occurs during a test configuration change or in response to a significant drop in yield.

The problem is that not all parts need to be maintained on the same schedule. Failing to clean some parts often enough can reduce yield, but not everything needs to be cleaned when it is scheduled.

“The key to changing any test process is showing a real economic value for the customer,” said Daniel Mu, manager of production value-added solutions for customers at Teradyne. “The customer will not do it for science. They do it to receive the benefit from the preventive or predictive maintenance. There is a high value in maintenance of consumables in the test cell, load board, needles, and sockets.”

Debris and probe wear
Each scrub of a probe needle on a die pad, and each socket connection with a DUT, creates friction between metal surfaces. Friction generates debris and wears the probe tips, pogo-pins, and sockets. In fact, the abrasive cleaning process contributes up to 95% of needle and socket tip wear. For probe tips, engineers must carefully plan cleaning events to maximize product yield while limiting tip wear. So on one hand, the less maintenance, the better.

But there’s a balance, because multi-site testing and more chip pins increase the contact force, friction, and debris levels. That, in turn can cause mis-testing, lower yield, and occasionally, device damage. Regularly scheduled cleaning of probe card needles and load board sockets is designed to prevent these occurrences. High levels of debris are the most prevalent causes of failures in probe cards and load boards.

“Most common failures are caused by accumulated debris (solder, copper, foreign material) on the probe tips. Other failure modes are probe wear, physical crashes, electrical discharge, or arcing,” said Darren James, technical account manager at Onto Innovation. Physical crashes can result from mishandling or prober/operator error.

As debris accumulates, the contact resistance rises. CRES is a key measure of wafer test effectiveness, and any increase subsequently can reduce yield or cause a faulty measurement of device performance parameters. The sudden appearance of foreign material on a socket can damage packaged units, as well, which is a particularly costly form of yield loss because it involves multiple chips. Cleaning removes the built-up debris on probe tips, contactors, and sockets.

To manage overall health of test interface boards, select control parameters are measured before, during, and after test. Typically, statistical process control (SPC) limits are set, and when those limits are exceeded, an alarm is sent from the test cell to the engineer to begin corrective action.

“These action plans are based on historical learning for product performance degradation characterization, such as material abrasive wear-out extrapolation,” said George Harris, vice president of global test services at Amkor. “These control limits are learned, studied, and characterized by the vendors and the users. They are both proactive, based on vendor product characterization, and reactionary, based on DUT metrics.”

Characterization to produce control limits and scheduled cleaning intervals provides an established process for all boards. But characterized limits are often based upon average or worst-case performance.

“When we established an AI team, we reviewed our customer’s processes looking for areas to apply these kinds of methodologies,” said Don Ong, head of innovation at Advantest. “At wafer probe, most of our customers follow a fixed cycle for cleaning, for example, every 5,000 touch downs. We considered that this is not very effective because the probe tips may not be that dirty, so we started looking into how we could make this adaptive.”

Additionally, characterized limit monitoring does not imply immediately response to an issue. IC suppliers of large SoCs bound for data centers would prefer rapid detection of potential device damage before it is tested. Damaged pins typically cannot be recovered, and the bumps on surface-mount devices may be irreparably damaged.

A dynamic cleaning approach requires engineers to determine the inputs and outputs of an algorithm. Adding a new test cell hardware module to assist with detection represents an even greater investment. As with any change in manufacturing, the roles of effectiveness, efficiency, and economy must be weighed.

Dynamic probe tip cleaning
Changing to a dynamic wafer probe cleaning routine is challenging because engineers need to identify parameters that absolutely indicate a cleaning is in order. Several parameters may correlate with dirty probe tips including contact resistance, DC voltage and current measurements, and yield.

But which parameters provide the best balance of low false negatives and false positives is not always obvious, given the complex interactions between the probing process and product yield variation. Engineers need to validate the process before shifting to a dynamic cleaning regimen in a production environment. The process also needs to be robust with respect to variations in a product’s characteristics.

Contact resistance appears to be an obvious choice, as this parameter indicates a good electrical contact prior to performing a test. Both DC and AC measurements change with a higher contact resistance. Yield also can decrease as debris accumulates at contact sites, in particular when comparing the yield on different test sites on a multi-site board.

“To anticipate optimal needle maintenance, we derive signals that are a combination of different measurements available in the ATE,” said Teradyne’s Mu. “We use parametric test data like contact resistance, voltage, and current to assess the contact quality, which is fairly straightforward. There are cases where the needles’ impact is ambiguous, and thus to reach a conclusion, more data and/or complex algorithms are required. The algorithm used depends on how complex the needle impact correlates with the data, and how fast we need to analyze the data and trigger the corrective actions. The best algorithm is chosen after experimentation and balancing these two factors — accuracy and speed.”

Measured parameters and changes in values or binning trends can indicate an issue.  But the ideal parameter needs to be evaluated and characterized on a product-by-product basis. With more engineering teams turning to machine learning for analysis, engineers are investigating ML approaches for cleaning frequency.

“Our goal in applying AI/ML was to implement a simple solution to do adaptive cleaning with machine learning,” said Advantest’s Ong. “We first looked into using contact resistance measured on each pin, because a pin with accumulated debris results in higher contact resistance. When we tried to implement it with one of our customers, we couldn’t get good results. In fact, the results we observed were actually pretty bad.”

What seemed obvious didn’t track well. Many factors contribute to CRES measurements, including prober overdrive.

“Next, we investigated binning trend, just simple pass/fail,” Ong said. “We adopted the random forest algorithm to look at the past few binning trends, and this approach correlated very well with when the probe card gets dirty. From there onward, we refined the solution.”

Fig. 1: Comparison between Fixed and Adaptive probe card cleaning. Source: Advantest

Fig. 1: Comparison between Fixed and Adaptive probe card cleaning. Source: Advantest


Fig. 1: Comparison between Fixed and Adaptive probe card cleaning. Source: Advantest

In both wafer and package testing, engineers use yield trend analysis to trigger for multiple issues. Cleaning can be one of those. An ML approach appears to bring a trigger that is highly correlated to the need for cleaning.

Advantest’s solution relies on comparing the pass/fail results between sites, which can only be done with multi-site probing. The methodology is applied on a wafer lot basis, and the first wafer provides the baseline of the pass/fail ratio for each site.  So unlike determining a fixed schedule cleaning, which requires characterizing a large volume of data over multiple lots, it bases its determination just on the first wafer in the lot. As a result, wafer lot processing variation is accounted for during the initial analysis of the first wafer. This very localized ML solution relies upon a small data set to determine the limits.

Customers that switched to this adaptive cleaning approach were able to substantially reduce the cleaning frequency, which prolonged probe card life by 2X (see figure 2). Advantest showed results for four products and a variety of probe needle types at the 2022 SW Test Symposium.

Fig. 2: Adaptive Probe Cleaning (APC) results for four  real production products.  Reduction ratio is the ratio of decreasing times of on-line cleaning to times of fixed cycle cleaning performed by a prober. Source: Advantest

Fig. 2: Adaptive Probe Cleaning (APC) results for four real production products.  Reduction ratio is the ratio of decreasing times of on-line cleaning to times of fixed cycle cleaning performed by a prober. Source: Advantest

In addition to improved needle lifetime, it reduces the disruption of cleaning. Any cleaning activity can impact the test process, so less cleaning time translates to more time spent on testing. That, in turn, improves overall equipment efficiency.

Socket cleaning
Just like probe tips, debris builds up on sockets and contactors in load boards, which adversely affects test results. Foreign material — also a product of metals rubbing — can cause shorts between pins. If the pins are located between the power and ground terminals, damage to the product and socket can occur. Foreign material also damages package pins or surface mount bumps. Such occurrences, if not caught immediately, can damage multiple units, increasing revenue loss.

A natural extension of adaptive probe cleaning is adaptive socket cleaning. However, because load boards are not as expensive as probe cards, the ROI has not prompted most IC manufacturers to do so. But for some IC suppliers, a socket contaminated with debris may have a significant enough impact that it motivates the company to invest in innovative detection techniques.

At the 2022 Advanced Semiconductor Manufacturing Conference, Intel engineers shared their work on implementing a real-time socket inspection system. “Defects or loose debris accumulated inside the socket can damage all subsequent units placed in socket until socket is cleaned/replaced,” the authors wrote. “To resolve this critical issue, we equipped each pick-and-place arm with a new machine vision system designed to fit inside the existing tool. The limited footprint constraints required a highly compact imaging system, which resulted in a variety of image artifacts, creating several unique challenges for the inspection system.”

These image artifacts required advanced algorithms to process the data. “We developed an inspection algorithm that utilizes a variety of advanced computer vision and machine learning techniques to normalize and match the images, remove artifacts, and detect defects. The flagged socket images can be manually dispositioned by the user and the socket can be sent for repair or cleaning as needed.”

The system searched for several socket issues including loose caps, loose caps with stain, loose pins, and foreign material. To be successful in a real-time environment they needed to complete the decision in less than 30 seconds, and successfully distinguish between real defects and image artifacts. The development of inspection image processing used a number of methods to ensure good image quality prior to the defect detection step. Qualification data for three products showed false positives to occur at a frequency of <0.1%. With the new inspection system, the Intel engineers reported they could quickly identify issues, prevent excursions, and ultimately Excellerate production yield.

Test board maintenance
Cleaning represents an activity of on-going maintenance. Test boards for wafer probe and package also require maintenance. Electro-mechanical relays wear out, capacitors’ values degrade, and the vias between a board’s layers can become open. When these issues occur, either the board can be repaired or fully replaced. Typically, engineers and technicians track yield for specific boards, and as yield decreases, they flag the board for repair.

Several industry experts noted that board complexity increases on a four-year cadence with pins and performance increasing by 2X. This results in more initial board failures, and more frequent repairs.

“There’s a natural defect rate to produce good working boards, such that as you continue to scale up the number of traces and the number of components, you’re going to see an increasing rate of failure as measured by first pass rate,” said Steve Ledford, general manager of device interface solutions at Teradyne. “Naturally, this results in a higher decay rate of failures to these boards over time.”

Waiting for yield to decrease before detecting a failing board risks revenue loss. Teradyne developed improved diagnostic techniques and programs to ensure only good boards were shipped, and boards on the brink of failure could be detected (see Figure 3). The methods can be used throughout the life of the board. The ability to predict when a board requires maintenance or retirement benefits product yield, quality, and total cost of ownership.

Fig. 3: A board maintenance and diagnostic program can achieve 95% fault coverage. Source: Teradyne

Fig. 3: A board maintenance and diagnostic program can achieve 95% fault coverage. Source: Teradyne

“We researched how we could use the tester to be a diagnostics tool,” Ledford said. “This is not a new concept. For decades, engineers have written board diagnostic programs. But we improved upon it by increasing our fault coverage rate up to 95%, compared to most engineers achieving between 70% to 80%. We have a very robust fault model library that is combined with a test library. A second major element is that we’ve automated the test program creation.”

The same board screening program can be used during test production to flag degradation in board characteristics. In effect, it becomes a continual monitor of board health that minimizes impact to product.

Trends in multi-site testing and increasing product pin counts greatly impact the total cost of ownership for probe cards and load boards. Improving the response to maintenance lowers the ownership cost and improves yield.

In wafer and package test facilities, real-time maintenance approaches can effectively detect the need for cleaning and predict the need for general board maintenance. Chipmakers use different approaches to correlate a test parameter with the need for cleaning or board maintenance. In one instance, engineers added cameras to image debris problems. While all of this requires engineering effort, the benefits of preventive cleaning processes and real-time action outweigh the cost of implementation.

Related Stories
Cleaning Up During IC Test
Dirty probe tips and sockets adversely affect test, which can impact chip reliability.

The Drive Toward More Predictive Maintenance
Using data for just-in-time maintenance for factories and ICs.

The Mighty Sensor In The Fab
Why regularly scheduled equipment maintenance is nearing the end, and what comes next.


  1. Edwards, A. Kumar, A. Vaske, N. McDaniel, D. Pradhan and D. Panda, “Real-Time Automated Socket Inspection using Advanced Computer Vision and Machine Learning : DI: Defect Inspection and Reduction,” 2022 33rd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC), 2022,

Mon, 07 Nov 2022 18:01:00 -0600 en-US text/html
Killexams : Nortel Networks

Campaign to Create Tomorrow

Learn more about The Ottawa Hospital's $500-million fundraising campaign, the largest in our city’s history, which will transform the future of healthcare in Ottawa.

Tue, 22 Nov 2022 15:13:00 -0600 en-US text/html
Killexams : The 5 worst things about my job as a software engineer
  • Gyasi Calhoun is a front-end software engineer and developer at Twilio.
  • While there are perks to software engineering, Calhoun says the industry can be stressful.
  • He says there is a ton of pressure to code outside of work and to make more and more money.

My dad always wanted me to become an engineer because he wanted to see me succeed. The industry has low unemployment rates and he thought I should always be able to find work. 

I listened to his advice and decided to become a computer science major in college and later become a software engineer.

I graduated about four years ago and since then I've worked as a full stack developer, a front-end web developer, a front-end engineer at JP Morgan Chase & Co, and a developer evangelist at Twilio — which I say is a cross between developing, marketing, and product management. 

I also create content for social media. On YouTube, I have 145,000 followers and I have 63,100 TikTok followers.

I talk more about what I like about software engineering more than about what I don't like. Sure, there are a lot of perks to being a software engineer such as six-figure salaries and free food, but some things are less than ideal. 

Here are the top 5 things I don't like about being a software engineer. 

1. It's stressful and you could burnout 

Programmers are often building things that have never been made before and there aren't references on how to do it. And it's incredibly exhausting work.

Plus, the more you move up the ladder as a programmer, the more expectations there are on top of your programming duties and it can feel like a never-ending growing list of things to do. It also doesn't help that most teams I've seen are undermanned. 

I know I've burned out when I stop feeling fulfilled or excited by my work. 

2. Pressure to learn at home

I think the reason many software engineers burn out is because there's pressure to code even when we're home. 

Some programmers will code at home to try and solve problems they don't know how to fix yet. And if you're not doing this, you may fall behind. Others work on projects they're passionate about do they're coding at night for fun. 

Also, technology moves so fast so you need to keep learning to stay up to date. There is this added pressure to constantly read blog posts, engage with open-source coding, and work on personal projects even when you're off the clock. 

I can't think of any other industry where you treat your job like a hobby as well. I like to do other things, like play basketball, and it's hard to find room for things outside of coding — there is an expectation that you need to eat, sleep, and breathe code all the time. 

3. Addiction to success 

There are so many videos about people making upwards of $120,000 right out of college or $200,000 in their twenties in this industry. That really pushes people to try and make as much money as they can and to jump from one job to another seeking more success. 

It's difficult to feel satisfied where you are professionally since there may be something better or higher paying somewhere else.

4. Technical interviews are exhausting 

When I'm preparing for technical interviews, I don't have time for anything else. I'm basically a student after 5 p.m. on top of my regular job. I also don't think technical interviews accurately show my, or anyone's, abilities. 

It was around the last week of December when I was preparing for my technical interviews. And on New Year's Eve, I could only celebrate with my wife and her family for a few minutes before returning to studying for a technical interview that was a week away. 

Plus, it's terrible to be rejected from a job opportunity on the 4th, 5th, or 6th round of interviews because you've already dedicated so much time just to be considered. 

5. There's a lot of imposter syndrome 

Programming is a competitive field but there are way more jobs than there are programmers. But there's a constant feeling that you may lose your job if you aren't the very best developer on your team. A lot of programmers end up with imposter syndrome and constantly compare themselves to their peers — which is really unhealthy.

If you are a software engineer, know that you bring value to the tech world and your company. And if you're feeling burnout, unfulfilled, or worried that you're not getting as much done as your peers, understand that programming ebbs and flows. It's extremely hard to even become a software engineer so think about how far you've come already.

The world needs problem solvers like software engineers and the opportunities for people in this industry are pretty much endless given the digital transformation the world is going through. I can't think of any other field that can compare as far as job security and the amount of high paying positions you can get. 

Fri, 25 Nov 2022 08:34:00 -0600 en-US text/html
Killexams : A chip to replace animal testing

New drugs made from nanoparticles that can easily penetrate any interface within our bodies are a great hope in medicine. For such hopefuls to reach the market, their safety must be ensured. In this context, it must also be clarified what happens if a substance manages to penetrate the natural barrier between baby and mother, the placenta, in the body of pregnant women.

"Environmental toxins can also pose a major threat to the sensitive fetus if they penetrate the placental barrier or disrupt the development and function of the placenta, thus indirectly harming the fetus," explains Tina Bürki, Empa researcher at the Particles-Biology Interactions lab in St. Gallen.

A team from Empa and ETH Zurich has been working for some time on the question of how this so-called embryotoxicity of substances can be determined precisely, simply and reliably. Now the team is developing a new system that will detect embryo-damaging substances without the need for animal testing.

A universe in a polymer case

At the heart of the process is a polymer , about the length of a human finger, that houses a small universe: Human cells grow on the chip that are to model the placental barrier and the embryo under conditions that are as close to reality as possible. For this purpose, cells of the placenta are cultivated on a porous membrane to form a dense barrier, and are formed into a tiny tissue sphere in a drop of nutrient solution.

To simulate blood circulation, a shaker continuously tilts the chip back and forth. Test substances can be added to the maternal side of the placenta. This allows the researchers to study the transport of the test substance and the effects on both tissues. "We already know that such a test system can work, as a simplified prototype was developed during a preliminary study with the Bio-engineering lab at ETH Zurich," says Bürki.

What is special about this new chip is that the researchers want to Excellerate the cell models by replacing the previously used laboratory cell lines or mouse cells with so-called primary human cells and a human stem cell line. "We are working closely with the gynecological clinic of the Cantonal Hospital of St. Gallen and can isolate the cells we are looking for from placental tissue that would otherwise be discarded after birth," Bürki explains.

The cells will be used to develop an improved three-dimensional placenta model. Ultimately, the embryo-placenta chip will allow the interaction of placenta and embryo to be reproduced and transport processes at the placenta as well as direct and indirect harmful effects of a substance on embryonic development to be investigated.

Alternative model advantageous

Studies on the developmental toxicity of drugs and environmental toxins currently rely on animal experiments with pregnant mice. In the EU, for example, 840,000 animals were used in toxicity and safety research in 2017, of which nearly 100,000 were used for developmental toxicity. Thanks to the new chip, the number of these animal experiments could be significantly reduced.

This is not only an important goal from an ethical point of view, because the significance of a test with pregnant mice is not optimal for assessing drug safety in humans: "The placenta has a very specific structure in each species—and in mice it is correspondingly different from that in humans," says Empa researcher Bürki. Better insights can be gained from the alternative in vitro model, i.e. the new system "in the ," because the new chip technology with primary can more reliably map what happens at the interface between mother and child.

Accelerating new therapies

The new is intended as a simple and precise way to check the safety of a substance early in the development of and thus accelerate the application of new therapies. In this way, the chip supports the safe-by-design principle, which envisions the early integration of safety aspects into the innovation process.

The need for developmental toxicity studies in industry is also increasing for another reason: The safety of chemicals and particles in the environment needs to be clarified, as required by the current REACH chemicals regulation. "The placenta embryo chip should ultimately be a user-friendly test kit that can provide important data on potential health risks during pregnancy," she said.

The project's results are also expected to help fill knowledge gaps in understanding the placental barrier. "The chip will be a model that brings together the processes at the and in the embryo. In this way, we hope to better understand the complex interactions that take place by means of signaling substances in the future," says Tina Bürki.

Citation: A chip to replace animal testing (2022, November 18) retrieved 9 December 2022 from

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Fri, 18 Nov 2022 01:58:00 -0600 en text/html
Killexams : Nortel alum-turned-mystery novelist combines her tech and writing background with Fictionary

Fictionary co-founder and CEO Kristina Stanley has worked in a wide variety of different jobs, from manager of broadband planning at Nortel to the director of employee, safety, and guest services for an Eastern British Columbia ski resort, to author of mystery novels.

But one of Stanley’s most difficult jobs was figuring out how to edit her own manuscripts while writing The Stone Mountain Mystery Series. As she told BetaKit in an interview, “it’s really, really difficult to edit a book from a story level. You’ve got thousands and thousands of elements that you have to keep track of and make them work together.”

“We’re trying to help the average person who doesn’t have an ‘in’ in the publishing industry get a really good book out there, get an agent, or get a publisher.”
-Kristina Stanley, Fictionary

Initially, Stanley tackled this problem using a combination of Microsoft Excel spreadsheets and graphs. But she soon realized that other authors likely faced the exact same issue, and set out to build a better way by combining her tech and writing background.

Today, Stanley’s software startup Fictionary aims to offer an alternative. Amid a wide field of solutions that help writers and editors with specific parts of the process, like spelling, grammar, style, structure, and publishing, Fictionary hones in on perhaps the most important and challenging part: producing a good story.

Fuelled by $1.8 million CAD in seed funding, Fictionary aims to help writers and editors around the world produce quality stories more quickly and affordably. With this capital, the Inverary, Ontario startup, based just north of Kingston, plans to move into non-fiction and start selling to other publishers and agencies to expand its community of users.

The startup’s all-equity round, which closed in September, was co-led by StandUp Ventures and BDC Capital’s Thrive Venture Fund, with support from The51 and a group of angels that includes Women’s Equity Lab general partner Sally Morris. For newly launched Thrive, Fictionary marks the fund’s third investment to date, after investing in Acerta and Private AI.

Stanley founded Fictionary in 2016 alongside her husband, Mathew (COO), who also previously worked at Nortel and has a background in tech, and her brother, Michael Conn, Fictionary’s former CTO, who has since left the company.

Initially, Fictionary focused solely on writers, before expanding to meet demand for a similar offering from editors. Today, Fictionary offers three subscription software products for writers and editors that range in price from $19 to $49 monthly, sells online courses, and provides a community for writers and editors to connect.

Fictionary’s software helps writers visualize their story arc by analyzing key story elements with artificial intelligence (AI) and gauging how their manuscript compares to fundamental storytelling components.

RELATED: With new Thrive platform, BDC commits half a billion dollars to invest in Canadian women-led startups and funds

“We’re trying to help the average person who doesn’t have an ‘in’ in the publishing industry get a really good book out there, get an agent, or get a publisher,” said Stanley.

On the editor side of the equation, the company claims its offering enables editors to provide better, deeper story edits in less time, increasing the quality and profitability of editors’ services.

The writing and editing software space features a ton of players, from Grammarly to Scrivener, Novel Factory, and Canada’s Wattpad. According to Stanley, Fictionary is unique within the sectors in terms of its focus on storytelling elements and its use of AI. “We’re it right now as far as, there’s an automated way to do this, and have software for it,” said Stanley.

“While there are other platforms endeavoring to address this gap in the market, there doesn’t appear to be a single player who is able to look at the writing and editing process in a comprehensive and meaningful way, which puts Fictionary at a sizeable advantage to lead the charge and expand into new markets and segments,” Michelle Scarborough, managing partner of BDC Capital’s Thrive Venture Fund, told BetaKit.

RELATED: StandUp Ventures reveals second fund dedicated to women-led startups with $30 million first close

Fictionary previously secured $100,000 in grant funding from Creative BC and raised $245,000 in pre-seed funding in 2019 from a group of angels that included Shopify co-founder Scott Lake, Stephanie Andrew of Women’s Equity Lab, and FirstEditing founder and CEO JoEllen Taylor.

According to Stanley, following that pre-seed round, Fictionary reached breakeven cash flow and had to decide whether to keep going on its current track or set its sights higher.

Following some discussions with StandUp Ventures, Fictionary decided to embark on a new chapter and raise more venture capital to tackle the opportunity it sees in this space amid the rise of self-publishing. “We have a great product, we’ve got product-market fit, we’ve got a market, so let’s just go for it,” said Stanley.

“The love for the product Fictionary users articulate so regularly is rare, and indicative of the power and impact the tool brings to its customers,” said StandUp Ventures senior associate Lucas Perlman, who is joining Fictionary’s board as part of the round. “The self-publishing world has exploded, and we believe Fictionary is poised to become a de-facto part of the story writing toolkit for writers and editors around the globe.”

RELATED: Wattpad’s new leader is focused on creator value

For her part, Scarborough said the Thrive Venture Fund sees “a sizeable opportunity [for Fictionary] in the fast-growing creator economy space—a market with many dimensions—within writing and editing, screenwriting, non-fiction, and beyond.”

To date, Fictionary has focused entirely on fiction but Stanley said the startup’s roadmap includes moving into non-fiction, where the CEO sees plenty of potential to apply its tech to helping people tell their own life stories. Fictionary also sees an opportunity to help agencies and publishers clear the slush pile of submitted manuscripts.

As it looks to build out its own community of writers and editors, Fictionary follows in the footsteps of Wattpad, which parlayed its vibrant self-publishing community of writers and readers—and the content produced by them—into a $754 million CAD acquisition last year.

After discussions with StandUp, Fictionary decided to embark on a new chapter.

“Wattpad is very inspirational for us,” said Stanley. “They are different in the sense that people write their stories in the community, where we help writers take those stories and turn them into powerful stories readers love. Their community is a great lead-in to Fictionary for writers needing to edit their stories.”

As the startup charts its growth strategy amid an uncertain economic environment, Stanley is confident that Fictionary is well-positioned to grow during this period, noting that people tend to write more when they are stressed. Back when COVID-19 first hit and everyone was cooped up, the CEO said people begin writing more, and demand for Fictionary rose. Heading into what could be a deep downturn, Stanley believes Fictionary is in a good spot given that it offers a tool to help people do their passion without spending a lot of money.

What Perlman finds most exciting is the appreciation Fictionary’s customers have for the startup’s product, noting that writers “pour countless hours into their stories and writing books is an emotional and very personal thing to take on.”

“Fictionary has removed a major hurdle that stopped these creators from bringing their stories into the world,” Perlman told BetaKit. “The impact of that really comes through when you speak to their customers and see feedback from their community.”

Feature image courtesy Fictionary.

Mon, 28 Nov 2022 21:00:00 -0600 Josh Scott en-CA text/html
Killexams : Here’s how a Twitter engineer says it will break in the coming weeks

On November 4, just hours after Elon Musk fired half of the 7,500 employees previously working at Twitter, some people began to see small signs that something was wrong with everyone’s favorite hellsite. And they saw it through retweets.

Twitter introduced retweets in 2009, turning an organic thing people were already doing—pasting someone else’s username and tweet, preceded by the letters RT—into a software function. In the years since, the retweet and its distant cousin the quote tweet (which launched in April 2015) have become two of the most common mechanics on Twitter.

But on Friday, a few users who pressed the retweet button saw the years roll back to 2009. Manual retweets, as they were called, were back.

The return of the manual retweet wasn’t Elon Musk’s latest attempt to appease users. Instead, it was the first public crack in the edifice of Twitter’s code base—a blip on the seismometer that warns of a bigger earthquake to come.

A massive tech platform like Twitter is built upon very many interdependent parts. “The larger catastrophic failures are a little more titillating, but the biggest risk is the smaller things starting to degrade,” says Ben Krueger,  a site reliability engineer who has more than two decades of experience in the tech industry. “These are very big, very complicated systems.” Krueger says one 2017 presentation from Twitter staff includes a statistic suggesting that more than half the back-end infrastructure was dedicated to storing data.

While many of Musk’s detractors may hope the platform goes through the equivalent of thermonuclear destruction, the collapse of something like Twitter happens gradually. For those who know, gradual breakdowns are a sign of concern that a larger crash could be imminent. And that’s what’s happening now.

It’s the small things

Whether it’s manual RTs appearing for a moment before retweets slowly morph into their standard form, ghostly follower counts that race ahead of the number of people actually following you, or replies that simply refuse to load, small bugs are appearing at Twitter’s periphery. Even Twitter’s rules, which Musk linked to on November 7, went offline temporarily under the load of millions of eyeballs. In short, it’s becoming unreliable. 

“Sometimes you’ll get notifications that are a little off,” says one engineer currently working at Twitter, who’s concerned about the way the platform is reacting after vast swathes of his colleagues who were previously employed to keep the site running smoothly were fired. (That last sentence is why the engineer has been granted anonymity to talk for this story.) After struggling with downtime during its “Fail Whale” days, Twitter eventually became lauded for its team of site reliability engineers, or SREs. Yet this team has been decimated in the aftermath of Musk’s takeover. “It’s small things, at the moment, but they do really add up as far as the perception of stability,” says the engineer.

The small suggestions of something wrong will amplify and multiply as time goes on, he predicts—in part because the skeleton staff remaining to handle these issues will quickly burn out. “Round-the-clock is detrimental to quality, and we’re already kind of seeing this,” he says. 

Twitter’s remaining engineers have largely been tasked with keeping the site stable over the last few days, since the new CEO decided to get rid of a significant chunk of the staff maintaining its code base. As the company tries to return to some semblance of normalcy, more of their time will be spent addressing Musk’s (often taxing) whims for new products and features, rather than keeping what’s already there running.

This is particularly problematic, says Krueger, for a site like Twitter, which can have unforeseen spikes in user traffic and interest. Krueger contrasts Twitter with online retail sites, where companies can prepare for big traffic events like Black Friday with some predictability. “When it comes to Twitter, they have the possibility of having a Black Friday on any given day at any time of the day,” he says. “At any given day, some news event can happen that can have significant impact on the conversation.” Responding to that is harder to do when you lay off up to 80% of your SREs—a figure Krueger says has been bandied about within the industry but which MIT Technology Review has been unable to confirm. The Twitter engineer agreed that the percentage sounded “plausible.”

That engineer doesn’t see a route out of the issue—other than reversing the layoffs (which the company has reportedly already attempted to roll back somewhat). “If we’re going to be pushing at a breakneck pace, then things will break,” he says. “There’s no way around that. We’re accumulating technical debt much faster than before—almost as fast as we’re accumulating financial debt.” 

The list grows longer

He presents a dystopian future where issues pile up as the backlog of maintenance tasks and fixes grows longer and longer. “Things will be broken. Things will be broken more often. Things will be broken for longer periods of time. Things will be broken in more severe ways,” he says. “Everything will compound until, eventually, it’s not usable.”

Twitter’s collapse into an unusable wreck is some time off, the engineer says, but the telltale signs of process rot are already there. It starts with the small things: “Bugs in whatever part of whatever client they’re using; whatever service in the back end they’re trying to use. They’ll be small annoyances to start, but as the back-end fixes are being delayed, things will accumulate until people will eventually just give up.”

Krueger says that Twitter won’t blink out of life, but we’ll start to see a greater number of tweets not loading, and accounts coming into and out of existence seemingly at a whim. “I would expect anything that’s writing data on the back end to possibly have slowness, timeouts, and a lot more subtle types of failure conditions,” he says. “But they’re often more insidious. And they also generally take a lot more effort to track down and resolve. If you don’t have enough engineers, that’s going to be a significant problem.” 

The juddering manual retweets and faltering follower counts are indications that this is already happening. Twitter engineers have designed fail-safes that the platform can fall back on so that the functionality doesn’t go totally offline but cut-down versions are provided instead. That’s what we’re seeing, says Krueger.

Alongside the minor malfunctions, the Twitter engineer believes that there’ll be significant outages on the horizon, thanks in part to Musk’s drive to reduce Twitter’s cloud computing server load in an attempt to claw back up to $3 million a day in infrastructure costs. Reuters reports that this project, which came from Musk’s war room, is called the “Deep Cuts Plan.” One of Reuters’s sources called the idea “delusional,” while Alan Woodward, a cybersecurity professor at the University of Surrey, says that “unless they’ve massively overengineered the current system, the risk of poorer capacity and availability seems a logical conclusion.”

Brain drain

Meanwhile, when things do go kaput, there’s no longer the institutional knowledge to quickly fix issues as they arise. “A lot of the people I saw who were leaving after Friday have been there nine, 10, 11 years, which is just ridiculous for a tech company,” says the Twitter engineer. As those individuals walked out of Twitter offices, decades of knowledge about how its systems worked disappeared with them. (Those within Twitter, and those watching from the sidelines, have previously argued that Twitter’s knowledge base is overly concentrated in the minds of a handful of programmers, some of whom have been fired.)

Unfortunately, teams stripped back to their bare bones (according to those remaining at Twitter) include the tech writers’ team. “We had good documentation because of [that team],” says the engineer. No longer. When things go wrong, it’ll be harder to find out what has happened. 

Getting answers will be harder externally as well. The communications team has been cut down from between 80 and 100 to just two people, according to one former team member who MIT Technology Review spoke to. “There’s too much for them to do, and they don’t speak enough languages to deal with the press as they need to,” says the engineer.

When MIT Technology Review reached out to Twitter for this story, the email went unanswered.

Musk’s recent criticism of Mastodon, the open-source alternative to Twitter that has piled on users in the days since the entrepreneur took control of the platform, invites the suggestion that those in glass houses shouldn’t throw stones. The Twitter CEO tweeted, then quickly deleted, a post telling users, “If you don’t like Twitter anymore, there is awesome site [sic] called Masterbatedone [sic].” Accompanying the words was a physical picture of his laptop screen open on Paul Krugman’s Mastodon profile, showing the economics columnist trying multiple times to post. Despite Musk’s attempt to highlight Mastodon’s unreliability, its success has been remarkable: nearly half a million people have signed up since Musk took over Twitter.

It’s happening at the same time that the first cracks in Twitter’s edifice are starting to show. It’s just the beginning, expects Krueger. “I would expect to start seeing significant public-facing problems with the technology within six months,” he says. “And I feel like that’s a generous estimate.”

Tue, 08 Nov 2022 06:31:00 -0600 en text/html
Killexams : American Nortel Communications, Inc. (ARTM)
U.S. markets close in 4 hours 1 minute





Other OTC - Other OTC Delayed Price. Currency in USD

0.01970.0000 (0.00%)

As of 09:53AM EST. Market open.


Time Period:
Dec 09, 2021 - Dec 09, 2022
Date Open High Low Close* Adj Close** Volume
Dec 09, 2022 0.0197 0.0197 0.0197 0.0197 0.0197 1,000
Dec 08, 2022 0.0209 0.0209 0.0197 0.0197 0.0197 2,400
Dec 07, 2022 0.0185 0.0202 0.0185 0.0202 0.0202 20,100
Dec 06, 2022 0.0209 0.0209 0.0197 0.0197 0.0197 11,500
Dec 05, 2022 0.0193 0.0209 0.0193 0.0209 0.0209 34,985
Dec 02, 2022 0.0180 0.0180 0.0137 0.0180 0.0180 135,330
Dec 01, 2022 0.0200 0.0200 0.0200 0.0200 0.0200 10,000
Nov 30, 2022 0.0205 0.0205 0.0205 0.0205 0.0205 -
Nov 29, 2022 0.0205 0.0205 0.0205 0.0205 0.0205 -
Nov 28, 2022 0.0205 0.0205 0.0205 0.0205 0.0205 100
Nov 25, 2022 0.0210 0.0210 0.0210 0.0210 0.0210 -
Nov 23, 2022 0.0210 0.0210 0.0210 0.0210 0.0210 100
Nov 22, 2022 0.0210 0.0210 0.0210 0.0210 0.0210 -
Nov 21, 2022 0.0235 0.0235 0.0210 0.0210 0.0210 36,257
Nov 18, 2022 0.0235 0.0235 0.0235 0.0235 0.0235 -
Nov 17, 2022 0.0235 0.0235 0.0235 0.0235 0.0235 -
Nov 16, 2022 0.0235 0.0235 0.0235 0.0235 0.0235 -
Nov 15, 2022 0.0235 0.0235 0.0235 0.0235 0.0235 -
Nov 14, 2022 0.0235 0.0235 0.0235 0.0235 0.0235 -
Nov 11, 2022 0.0235 0.0235 0.0235 0.0235 0.0235 -
Nov 10, 2022 0.0235 0.0235 0.0235 0.0235 0.0235 1,800
Nov 09, 2022 0.0210 0.0210 0.0210 0.0210 0.0210 6,000
Nov 08, 2022 0.0210 0.0210 0.0210 0.0210 0.0210 -
Nov 07, 2022 0.0210 0.0210 0.0210 0.0210 0.0210 750
Nov 04, 2022 0.0223 0.0223 0.0220 0.0220 0.0220 270
Nov 03, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 -
Nov 02, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 -
Nov 01, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 -
Oct 31, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 -
Oct 28, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 -
Oct 27, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 16,000
Oct 26, 2022 0.0240 0.0240 0.0240 0.0240 0.0240 -
Oct 25, 2022 0.0240 0.0240 0.0240 0.0240 0.0240 -
Oct 24, 2022 0.0224 0.0240 0.0224 0.0240 0.0240 200
Oct 21, 2022 0.0240 0.0240 0.0240 0.0240 0.0240 -
Oct 20, 2022 0.0240 0.0240 0.0240 0.0240 0.0240 -
Oct 19, 2022 0.0240 0.0240 0.0240 0.0240 0.0240 -
Oct 18, 2022 0.0240 0.0240 0.0240 0.0240 0.0240 -
Oct 17, 2022 0.0240 0.0240 0.0240 0.0240 0.0240 -
Oct 14, 2022 0.0240 0.0240 0.0240 0.0240 0.0240 1,850
Oct 13, 2022 0.0221 0.0221 0.0221 0.0221 0.0221 -
Oct 12, 2022 0.0221 0.0221 0.0221 0.0221 0.0221 -
Oct 11, 2022 0.0221 0.0221 0.0221 0.0221 0.0221 -
Oct 10, 2022 0.0221 0.0221 0.0221 0.0221 0.0221 -
Oct 07, 2022 0.0221 0.0221 0.0221 0.0221 0.0221 -
Oct 06, 2022 0.0221 0.0221 0.0221 0.0221 0.0221 -
Oct 05, 2022 0.0240 0.0240 0.0221 0.0221 0.0221 5,100
Oct 04, 2022 0.0240 0.0240 0.0240 0.0240 0.0240 2,000
Oct 03, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 -
Sep 30, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 -
Sep 29, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 -
Sep 28, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 -
Sep 27, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 -
Sep 26, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 -
Sep 23, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 -
Sep 22, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 7,900
Sep 21, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 -
Sep 20, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 -
Sep 19, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 -
Sep 16, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 -
Sep 15, 2022 0.0221 0.0221 0.0220 0.0220 0.0220 51,400
Sep 14, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 10,000
Sep 13, 2022 0.0230 0.0230 0.0230 0.0230 0.0230 -
Sep 12, 2022 0.0230 0.0230 0.0230 0.0230 0.0230 -
Sep 09, 2022 0.0230 0.0230 0.0230 0.0230 0.0230 -
Sep 08, 2022 0.0230 0.0230 0.0230 0.0230 0.0230 -
Sep 07, 2022 0.0230 0.0230 0.0230 0.0230 0.0230 -
Sep 06, 2022 0.0230 0.0230 0.0230 0.0230 0.0230 -
Sep 02, 2022 0.0230 0.0230 0.0230 0.0230 0.0230 -
Sep 01, 2022 0.0230 0.0230 0.0230 0.0230 0.0230 -
Aug 31, 2022 0.0230 0.0230 0.0230 0.0230 0.0230 -
Aug 30, 2022 0.0230 0.0230 0.0230 0.0230 0.0230 -
Aug 29, 2022 0.0230 0.0230 0.0230 0.0230 0.0230 -
Aug 26, 2022 0.0230 0.0230 0.0230 0.0230 0.0230 1,385
Aug 25, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 -
Aug 24, 2022 0.0220 0.0220 0.0220 0.0220 0.0220 500
Aug 23, 2022 0.0210 0.0210 0.0210 0.0210 0.0210 -
Aug 22, 2022 0.0210 0.0210 0.0210 0.0210 0.0210 -
Aug 19, 2022 0.0210 0.0210 0.0210 0.0210 0.0210 1,063
Aug 18, 2022 0.0210 0.0210 0.0210 0.0210 0.0210 -
Aug 17, 2022 0.0210 0.0210 0.0210 0.0210 0.0210 -
Aug 16, 2022 0.0210 0.0210 0.0210 0.0210 0.0210 -
Aug 15, 2022 0.0210 0.0210 0.0210 0.0210 0.0210 374
Aug 12, 2022 0.0200 0.0200 0.0200 0.0200 0.0200 -
Aug 11, 2022 0.0200 0.0200 0.0200 0.0200 0.0200 -
Aug 10, 2022 0.0340 0.0340 0.0200 0.0200 0.0200 3,213
Aug 09, 2022 0.0290 0.0290 0.0290 0.0290 0.0290 -
Aug 08, 2022 0.0250 0.0300 0.0250 0.0290 0.0290 59,000
Aug 05, 2022 0.0347 0.0347 0.0347 0.0347 0.0347 -
Aug 04, 2022 0.0347 0.0347 0.0347 0.0347 0.0347 1,000
Aug 03, 2022 0.0290 0.0290 0.0290 0.0290 0.0290 -
Aug 02, 2022 0.0350 0.0350 0.0290 0.0290 0.0290 600
Aug 01, 2022 0.0240 0.0240 0.0240 0.0240 0.0240 -
Jul 29, 2022 0.0240 0.0240 0.0240 0.0240 0.0240 -
Jul 28, 2022 0.0240 0.0240 0.0240 0.0240 0.0240 115
Jul 27, 2022 0.0280 0.0280 0.0280 0.0280 0.0280 -
Jul 26, 2022 0.0280 0.0280 0.0280 0.0280 0.0280 -
Jul 25, 2022 0.0280 0.0280 0.0280 0.0280 0.0280 -
Jul 22, 2022 0.0280 0.0280 0.0250 0.0280 0.0280 61,550
Jul 21, 2022 0.0280 0.0360 0.0280 0.0360 0.0360 18,060
*Close price adjusted for splits.**Adjusted close price adjusted for splits and dividend and/or capital gain distributions.

Loading more data...





Thu, 01 Dec 2022 10:00:00 -0600 en-US text/html
Killexams : Elon Musk got into an argument with an engineer, then publicly fired him

Less than a week after laying off thousands of Twitter employees, new owner Elon Musk is firing staffers who disagree with him — sometimes publicly.

On Monday, Musk tweeted that he fired an engineer at the company who had publicly disagreed with him about the Twitter app.

Musk had tweeted an apology for the app being "super slow" in some countries, to which engineer Eric Frohnhoefer replied, saying, "I have spent ~6yrs working on Twitter for Android and can say this is wrong."

Musk then challenged Frohnhoefer, saying, "Twitter is super slow on Android. What have you done to fix that?" 

Frohnhoefer replied with a detailed thread about changes he had made to Excellerate the app, and suggested deleting some features to speed up loading time.

The exchange was met with incredulity from Twitter users that a CEO and staffer would argue publicly about a product feature. Shortly after, Musk tweeted, "He's fired." 

Frohnhoefer responded with a salute emoji, later tweeting a photograph of a locked laptop screen.

Frohnhoefer didn't immediately respond to a request from CBS MoneyWatch for comment.

Frohnhoefer appears to be the first of several outspoken employees to get the ax. On Tuesday, tech publication Platformer reported that 20 engineers who had criticized Musk in internal Slack channels had been fired via email.

"We regret to inform you that your employment is terminated effective immediately. Your accurate behavior has violated company policy," now-former workers were told via email, according to screenshots posted on Twitter.

On Tuesday, Musk deleted the tweet in which he fires Frohnhoefer, but it remains unclear if that revokes his termination. He also tweeted a mocking reply to reports of the fired engineers.

"I would like to apologize for firing these geniuses. Their immense talent will no doubt be of great use elsewhere," Musk said.

Twitter's media relations team, which has been disbanded, according to multiple media reports, did not respond to a request for comment. 

Since Musk took ownership of Twitter, he has lauched, then paused, a plan to open its blue-check verification system to anyone paying $8 a month, which led to a free-for-all of impersonators on the platform. Several large advertisers have fled the platform over concerns about moderation and hate speech. After Tuesday's firings, some users wondered how long a company could keep running after eviscerating its staff.

Tue, 15 Nov 2022 00:44:00 -0600 en-US text/html
Killexams : Ex-Twitter Engineer Accuses Twitter of Retaliation for Helping Doomed Coworkers

Photo: David Odisho (Getty Images)

One of the nearly 4,000 Twitter employees laid off in the company‘s tumultuous post-Elon Musk acquisition says the company illegally targeted him for trying to help fellow employees save documents prior to their abrupt removal from the company.

Former Twitter engineer Emmanuel “Manu” Cornet reportedly filed a complaint with the National Labor Relations Board on Monday accusing them of retaliatory actions days after Musk took the helm as CEO. That firing, according to the complaint, came in response to a Google Chrome extension Cornet built and shared with employees that let them get emails from their Gmail accounts. Twitter haphazardly moved to lay off around half of its global workforce last week and has already reportedly had to beg some of those workers to return.

Cornet detailed some of the time leading up to his firing on his personal blog. With rumors of mass layoffs circling Twitter’s online channels, Cornet says he decided to upload his email downloading tool to the Google Play Store and then sent a copy of that link to a Twitter Slack channel. Workers, now in hindsight rightfully fearful of sudden layoff calls from their new boss, could use the tool to get important documents like performance reviews, stock statements, key proofs of achievement and other human resources documents.

“Think about it: if you thought you may lose access to all your work email tomorrow, is there anything in there that you may need?” Cornet said.

Twitter allegedly saw things differently. Cornet, in the complaint and on his blog alleges Twitter fired him the same day he shared the extension link on Slack. The post containing the link was also allegedly taken down. Cornet published a redacted version of his termination email which said his, “recent behavior has violated multiple policies.”

Twitter did not immediately respond to Gizmodo’s request for comment.

Cornet has had a busy few days away from Twitter. Last week, he was the lead plaintiff in a class action lawsuit accusing Twitter of potentially violating federal and state laws requiring companies generally to provide at least 60 days of advance notice for major layoffs.

“A couple of people much smarter than me have suggested that that this may be an excuse to fire me over a ‘troublemaker’ vibe coming from me,” Cornet said on his blog. “I don’t deny that, and I don’t blame the new management for preferring not to have to deal with that liability.”

The new complaint comes on the heels of another unfair labor complaint filing, this time by the Alphabet Workers Union, which accused Google of illegally preventing contract workers from accessing an online “Share my Salary” spreadsheet showing workers pay rates. The AWU says hundreds of workers had submitted pay details to that spreadsheet since it was created in 2021 in an effort to bolster workplace transparency. According to the AWU, Alphabet withdrew access to that spreadsheet on July 14, leaving as many as 50,000 workers locked out of the file.

“It’s clear that Alphabet and its various affiliates do not want workers to be armed with knowledge regarding pay rates across the company,” Alphabet Workers Union Organizing Chair Shelby Hunter said in a statement. “Every Alphabet worker, including Temporary, Vendor and Contract workers, have a right to pay transparency and fair wages.”

Tue, 08 Nov 2022 08:02:00 -0600 en text/html
Killexams : Apple Engineer Addresses Lack of Lossless Support on New AirPods Pro

An Apple engineer has addressed the lack of lossless audio support in the second-generation AirPods Pro in a new interview.

airpods pro 2
Current Bluetooth technology in the AirPods lineup means that Apple's audio products do not support Apple Music Lossless audio. Apple has previously hinted that it may develop its own codec and connectivity standard that builds on AirPlay and supports higher quality audio streaming, but so far has not made any such move. ‌

‌Apple Music‌‌ offers lossless streaming which is 24-bit and up to 48KHz, and high-res lossless which goes up to 192KHz and requires an external digital-to-analog converter.

In an interview with What Hi-Fi?, Apple engineer Esge Andersen, who works on the company's acoustic team, said that Apple does not believe that current Bluetooth technology is a limiting factor in audio quality for the AirPods. Anderson added that even with current Bluetooth technology and codec standards, Apple can still make improvements in audio quality while the company's focus remains on reliability.

Andersen remains coy, saying that while audio quality is always a priority, "it is important to understand that we can still make big strides without changing the codec. And the codec choice we have there today, it's more about reliability. So it's about making something robust in all environments."

"We want to push the sound quality forward, and we can do that with a lot of other elements. We don't think that the codec currently is the limitation of audio quality on Bluetooth products."

During the interview, Anderson also offered an interesting look into how Apple developed the new second-generation ‌AirPods Pro‌ and how it validates sound quality. Anderson revealed that Apple has a panel of "sound experts" that offer Apple's engineers feedback on audio quality. "And at the end of the day, there is somewhat of a compromise, because you can't make it perfect for everybody yet," he said.

One of the most considerable improvements with the new second-generation ‌AirPods Pro‌ is better Active Noise Cancellation. Apple says that ANC on the new ‌AirPods Pro‌ is up to 2x better than before. Anderson said Apple was pushed to make this large improvement because it wanted "to give everybody an AirPods Max in their pocket."

Fri, 25 Nov 2022 05:14:00 -0600 en text/html
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