After shuttering and liquidating 115 locations earlier this year, the Buybuy Baby plans to reopen 11 locations in five states this fall.

Buybuy Baby is back: Retailer to reopen 11 stores after Bed, Bath & Beyond bankruptcy

Troubled retailers aren't in the clear this holiday season as those burdened with a heavy debt load could find it too difficult to reverse. Why it matters The more expensive financing environment is unlikely to improve the situation for those in distress.

When debt comes knocking at troubled retailers

Meme stocks are often thought of as a joke, but what if you can actually leverage them into something worthwhile?

Retail And Algo Trading: The New Giants Of The Financial World

After parent company Bed Bath & Beyond filed for bankruptcy this year, some buybuy Baby stores will return. Here's where, and when.

Buybuy Baby will reopen next month in Delaware, and raffle off free cribs and strollers

The National Retail Federation expects Halloween spending this year to reach a record $12.2 billion, exceeding last year's record of $10.6 billion, according to the annual survey conducted by Prosper Insights & Analytics.

Halloween spending projected to hit record high this year

Spirit Halloween, based in Egg Harbor Township, New Jersey, lists 20 Minnesota locations on its website. Fifteen are in the metro area, including at Southdale Center in Edina, Har Mar Mall in Roseville and a former Bed Bath & Beyond space in Maple Grove. The company has been at it for 40 years and has over 1,500 locations across the country.

Spirit Halloween has 20 stores in Minnesota, boosting underused shopping centers

Buy Buy Baby will return under new ownership. The Cherry Hill location is among several stores returning in the coming weeks.

Buy Buy Baby In Cherry Hill To Reopen Soon

After purchasing the intellectual property rights of the baby-focused banner for $15.5 million in July, Piscataway-based Dream On Me Inc. says it plans to launch 100 to 120 brick-and-mortar shops over the next three years.

Buybuy Baby’s November comeback includes 4 NJ stores

Get the most recent info and news about Bed Bath & Beyond on HackerNoon, where 10k+ technologists publish stories for 4M+ monthly readers.

Bed Bath & Beyond Inc., together with its subsidiaries, operates a chain of retail stores. The company sells a range of domestics merchandise, including bed linens and related items, bath items, and kitchen textiles; and home furnishings, such as kitchen and tabletop items, fine tabletop, basic housewares, general home furnishings, consumables, and various juvenile products. It also provides various textile products, amenities, and other goods to institutional customers in the hospitality, cruise line, healthcare, and other industries. As of February 29, 2020, the company had 1,500 stores, including 976 Bed Bath & Beyond stores in the United States and Canada; 261 stores under the names of World Market, Cost Plus World Market, or Cost Plus; 126 Buy Buy BABY stores; 81 stores under the Christmas Tree Shops, Christmas Tree Shops andThat! Names; and 53 stores under the Harmon, Harmon Face Values, or Face Values names. It also offers products through various Websites and applications, such as bedbathandbeyond.com, bedbathandbeyond.ca, harmondiscount.com, facevalues.com, christmastreeshops.com, andthat.com, buybuybaby.com, buybuybaby.ca, harborlinen.com, t-ygroup.com, worldmarket.com, personalizationmall.com, and decorist.com. In addition, it operates PersonalizationMall.com, an online retailer of personalized products; and Decorist, an online interior design platform. The company was founded in 1971 and is headquartered in Union, New Jersey.

Bed Bath & Beyond

Github Motion to dismiss Court Filing, retrieved on January 26, 2023 is part of . You can jump to any part in this filing . This part is 20 of 26. HackerNoon’s Legal PDF Series here ARGUMENT IV. PLAINTIFFS’ TORT AND UCL CLAIMS FAIL. B. Plaintiffs Do Not Plausibly Allege A Contract Or Business Expectancy, Nor Defendants’ Knowledge Of One As Required For An Interference With Economic Advantage Claim. Plaintiffs’ tortious interference claim (Count III) against GitHub and Microsoft is deficient in multiple other ways. “Tortious interference with contractual relations requires (1) the existence of a valid contract between the plaintiff and a third party; (2) the defendant’s knowledge of that contract; (3) the defendant’s intentional acts designed to induce a breach or disruption of the contractual relationship; (4) actual breach or disruption of the contractual relationship; and (5) resulting damage.” Ixchel Pharma, LLC v. Biogen, Inc., 9 Cal. 5th 1130, 1141 (2020) (quotation marks omitted). The Complaint falls short on every element. Although Plaintiffs label their claim one for tortious interference with contract, they identify no contractual relationship between themselves and anyone else—much less a contract that GitHub and Microsoft knew about. See Compl. ¶¶ 188-93; see also Bed, Bath & Beyond of La Jolla, Inc. v. La Jolla Vill. Square Venture Partners, 52 Cal. App. 4th 867, 878 (1997) (plaintiff must allege an existing, enforceable contract). While Plaintiffs allege that they deposited materials in public GitHub repositories subject to open source licenses, they do not allege that any third party ever entered into a contract with them in regard to those materials. Nor do Plaintiffs plausibly allege that GitHub or Microsoft committed “intentional acts designed to induce a breach or disruption” or “actual breach or disruption” with respect to an open source license granted by Plaintiffs to any unidentified third party. Ixchel, 9 Cal. 5th at 1141. All they allege is that “[a]t GitHub’s upcoming yearly conference, GitHub Universe 2022, it will host a presentation called ‘How to compete with open source—and win.’” Compl. ¶ 190. Plaintiffs construct their claim on a tortured interpretation of this title, as though the presentation provides a blueprint on how to compete against open source, when the more natural reading is that it is about how to compete effectively using open source. But in all events, this is hardly an allegation of a specific act to knowingly interfere with specific contracts. And in any event, “compet[ing]” and “win[ning]” is not a tort. See Ixchel, 9 Cal. 5th at 1142. The Complaint therefore states no claim for intentional interference with contract against GitHub or Microsoft. The Complaint also fails to state a claim for the related tort of interference with prospective economic advantage. Although “[t]ortious interference with prospective economic advantage does not depend on the existence of a legally binding contract,” it still requires a plaintiff to “show that the defendant knowingly interfered with an economic relationship between the plaintiff and some third party, which carries the probability of future economic benefit to the plaintiff.” Ixchel, 9 Cal. 5th at 1141 (cleaned up). Specific known relationships must be identified. Westside Ctr. Assocs. v. Safeway Stores 23, Inc., 42 Cal. App. 4th 507, 523-28 (1996); Rosen v. Uber Techs., Inc., 164 F. Supp. 3d 1165, 1178-79 (N.D. Cal. 2016). Here, Plaintiffs fail to allege any specific relationship with a reasonably likely economic benefit that GitHub and Microsoft knew about and intended to interfere with. The Complaint merely asserts that “Defendants have wrongfully interfered with the business interests and expectations of Plaintiffs and the Class by improperly using Copilot to create Derivative Works that compete against OSC.” Compl. ¶ 189. This conclusory “the-defendant-unlawfully-harmedme accusation,” Iqbal, 556 U.S. at 678, does not identify the “economic relationship” supposedly interfered with or plausibly allege the “probability of future economic benefit” claimed to be disrupted. Nor does the Complaint allege “actual disruption” or specific “harm,” two additional elements of the claim. Korea Supply Co. v. Lockheed Martin Corp., 29 Cal. 4th 1134, 1153 (2003). As a result, the Complaint does not state a claim for any economic interference tort. Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case 4:22-cv-06823-JST retrieved on September 11, 2023, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. documentcloud.org

GitHub, Microsoft Had No Contractual Obligation to Programmers Whose Code They Used to train Copilot

Most of the modern and successful agile organizations are increasingly relying upon the new insights gained by third-party data to complement their internal and first-party data to make smarter business decisions. Users can adapt to dynamic business models as layering data from multiple third-party sources enable them to do so. This ultimately optimizes customer success. With AWS Data Exchange, organizations can accelerate their capabilities to make smarter business decisions, enabling them to make more informed and data-infused decisions faster. This blog is aimed at guiding users to understand how they can leverage AWS SageMaker, AWS Marketplace, and AWS Data Exchange to deduce smarter and actionable business decisions from third-party data. AWS Data Exchange can be leveraged by customers to optimize efficiency, minimize costs and accelerate their business outcomes. The end users can subject the third-party data to: ·       Write algorithms to train custom machine learning (ML) models ·       Develop models to dashboard highly localized data points that impact operational decision making &/ business continuity ·       Extract more value from the data points such as from propriety data to support point of sale (POS), supply chain, human resources, customer loyalty, and other business functions ·       Pilot new technologies at a minimal investment upfront ·       Solve a process challenge that could be detrimental to your customer satisfaction indexes ·       Leverage a data mesh to solve regulatory reporting challenges related to data ownership, governance, and lineage For the majority of the B2B professionals, optimizing their customers’ experiences is synonymous with engineering a proper framework for . decoupled data regulation According to an estimate by McKinsey Global Institute, data and analytics can generate value worth between $9.5 trillion and 15.5 trillion a year if embedded at scale. Let’s now inspect how AWS SageMaker, AWS Marketplace, and AWS Data Exchange can be used to predict the popularity of retail products and can help retail organizations make more informed business decisions with data sets in conjunction with advanced analytics and machine learning. How to Leverage AWS SageMaker, AWS Marketplace, and AWS Data Exchange to Predict the Popularity of Retail Products Certainly leveraging advanced analytics, data visualization tools, and machine learning algorithms helps many retail customers gain a competitive edge. To scale up your machine learning and analytics, however, you need access to high-quality data sets, or else it would be the same “Garbage in, garbage out” theory. Some of the data is available in-house. However, data scientists always need high-quality, third-party data in addition to the data that’s already available for analysis. With the help of AWS Data Exchange, it gets easier for customers to find, subscribe to, and use third-party data in AWS. AWS Data Exchange boasts of having more than 2,000 data products from over 100 qualified data providers. The users can subscribe, download or load data into Amazon S3 buckets and analyze them with the help of AWS analytics and ML services. The popularity of retail products can be predicted using a dataset from AWS Data Exchange. One also can use Amazon SageMaker and a third-party algorithm available in AWS Marketplace to analyze data and generate actionable business insights. Let’s consider an experiment designed by AWS. How to Deliver a Custom ML Model to Predict the Popularity of Bath Products: The Retail Angle An ML startup using Decision Support System (DSS) was approached by a customer, a retail store to deliver a custom ML model to predict the popularity of bath products. The goal for the startup was simple: to help increase sales and store revenues by stocking the most popular products. The solution architect at the startup had to create a custom ML model to advise on the products that had to be stocked in order to boost sales. The solution architect had to create an ML model to predict the popularity of bath products based on attributes such as the product name and category. The retail client had already purchased the from AWS, which contains the real-world datasets for bath products comprised of data from large chains such as Bath & Body Works and Bed Bath & Beyond. The solution architect used Intel’s DAAL decision forest classification algorithm, available in AWS Marketplace, for training a machine learning model. Retail data set package The experiment was designed as under: ·       The solution architect got permission to use AWS Data Exchange and allied services to subscribe and export datasets by associating AWSDataExchangeSubscriberFullAccess AWS Data managed policy with his IAM principal. This gave the architect the necessary permissions needed to use AWS Data Exchange as a subscriber. ·       Leveraging , the solution architect ensured that he had access to S3 bucket, to which the dataset was to be exposed. Identity and Access management in AWS Data Exchange ·       The architect ensured access to S3 bucket where the dataset was to be exported. ·       The architect acquainted himself with the basic philosophies of AWS Exchange concepts. ·       Finally, the architect ensured that the IAM principal had managed IAM policy associated. AmazonSageMakerFullAccess An Overview of the Solution Since the retail client had already procured the dataset, the next logical step was to transfer the dataset into an S3 bucket. The client transferred the data to an S3 bucket with the help of documentation. Data providers often provide updated revisions of their datasets. To ensure that the solution architect was using the latest version, the client set up a process to automatically load the new data from AWS Data Exchange into the S3 bucket. This process was set up using documentation from AWS. See more. The solution architect opted for a three-step approach: Subscribing to the Third-Party Algorithm Available in AWS Marketplace – This is an optional step as marketers can use any algorithm for training a model. Setting Up the AWS SageMaker Notebook Instance – Creation of the notebook instance enabled compiling of the codes, which was intrinsic to data preparation. Custom Model Training – This step involved the use of third-party data and algorithms. Testing of the Model – This step involved the use of Ginger orange 3-wick candle as the product name, and the ML model predicted whether this model would be popular. Let’s discuss each of the 4 steps described above in detail: Step 1: Subscribe to the Algorithm To subscribe to the Intel®DAAL DecisionForest Classification algorithm in AWS Marketplace, the following steps can be used: a)      Open the Intel®DAAL DecisionForest Classification listing in AWS Marketplace. b)      Read the and and note the supported instance types. Highlights, Product Overview, Usage Information, Additional resources c)       The option was selected. Continue to Subscribe d)      The architect reviewed the End-user license agreement, Support Terms, and Pricing Information and selected Accept Offer to agree to the pricing, EULA, and support terms of the listing. In this step, the other methods that can be used to train your machine learning model apart from Intel®DAAL DecisionForest Classification algorithm include built-in Amazon SageMaker algorithms that support classification, such as the , , and other algorithms available in major supported for training your machine learning model. LinearLearner algorithm XGBoost algorithm frameworks Step 2: Creating an AWS SageMaker Notebook Instance The architect to analyze the data and train the machine learning model to predict popular bath products. The following steps were performed in the notebook: created SageMaker notebook instance 1.       Data Analysis and Feature Engineering The architect identified interesting features such as looking at the dataset to explore features such as price, name, category, reviews, how well the product was received in the market and how long it lasted, ratings and promotions applied. ·       The architect kept the model simple chose the and as features. name category ·       The architect combined the review counts, review ratings, and the duration for which the product lasted in the market. A single variable was created that implied whether the product became popular or not. outcome ·       The architect cleansed the data and cleansed the product name feature by removing all special characters and converting numerals to words. The text case was changed to lowercase, and the insignificant null values were removed. ·       Some new features were created, and the data showed that popular products had shorter names. The architect created a product-name-length feature. ·       The architect found the categories to be really broad. For example, three-wick-candle and were in the same category. The architect decided to extract all common suffixes to create a new feature called a . single-wick-candle sub-category ·       The embeddings were generated. The product name column itself generated embeddings, and the architect visualized the embeddings via t-SNE plot. 2.       Data Preparation for Training ·       Many algorithms accept data only in numeric format. The solution architect used one such algorithm, and one-hot encoded the category and subcategory features. ·       The dataset was randomized and split into training and testing datasets and then uploaded to S3. 3.       Hyperparameter Specification As Per the Algorithmic Specification to Run a Training Job For training, the data was used from the S3 bucket of the architect. The algorithm was harnessed from the AWS Marketplace, and hyperparameters were specified by the architect to train the ML model. ·       The architect specified values for hyperparameters and then trained a model with 70% accuracy. ·       Once the model was trained, there were two options: A)      Performing a batch inference. B)      Standing up an Amazon SageMaker endpoint for performing real-time inference. For this task, the architect stood up an Amazon SageMaker endpoint. 4.       Testing the Trained Model ·       When the architect entered Ginger orange 3-wick candle as the product name, the ML model deduced whether it would be popular or not. ·       Then, the architect tweaked product names to a few other combinations, such as Orange vanilla hand soap and Orange hand soap. ·       The model was further tuned by hyperparameter adjusting and optimization to achieve higher accuracy results. ·       The architect continued performing inference on the tuned model until he had a list of products and categories to recommend to the client. Alternative Approaches The architect could further extend the exercise by adjusting features such as price and promotions. He could also enable additional synthetic features based on the frequency of occurrences of the specific fragrant elements. For instance, he could have predicted whether lavender-or coconut-scented products were more likely to be popular. Wrap Up This post demonstrates a scenario wherein a solution architect could deliver a custom ML model to predict the popularity of retail bath products to for the client. optimize the sales revenue The retail client was advised to stock specific products based on the model created. One can use relevant real-world third-party data and algorithms to effectively train a custom ML model. One can even list and monetize the trained ML models, depending on the terms of use of third-party products one procured from AWS Marketplace. One can get information about Amazon SageMaker Algorithms and Model Packages by . While AWS Data Exchange enables you to find, subscribe to, and use data products. One can build machine learning workflows with AWS Data Exchange and AWS SageMaker. AWS Data Exchange also allows the users to retrieve new updates automatically. referring to the AWS documentation Finally, one can use AWS Marketplace for machine learning workloads.

Predicting Popularity of Retail Products Using AWS SageMaker, AWS Marketplace & AWS Data Exchange

Augmented reality might turn out to be one of the big winners of the coronavirus crisis: People need more fun in their lives, and brands need new ways to attract customers. And since most AR experiences require only a smartphone, they are cheaper and more accessible than VR. From animated tattoos to interactive models of office spaces, here are 10 innovative studios bringing AR into our everyday lives. 1) Aircards Aircards creates fun and engaging marketing merchandise – in particular, business cards, as the name suggests. When you scan the QR code on a business card, it comes alive. For instance, you might see the card's owner talking to you, suggesting that you follow him or her on social media. The company also makes AR marketing fliers, banners, billboards, and packaging. 2) ARzilla ARzilla keeps finding new ways for customers to interact with products, especially through WebAR and social AR. When clients explore AR experiences integrated into a brand's website, they start to associate the feeling of excitement and fun with the brand. All of ARzilla's experiences are web-based: You can access them from any smartphone without downloading an app. ARzilla also designs viral filters and masks that boost brand awareness, flyers, banners, packaging, etc. The team works with various platforms (Zappar, 8th Wall, Spark AR), as well as creates custom-coded experiences. 3) Arfected Arfected creates shareable content that increases brand awareness and engagement. In addition to web-based experiences and apps, it works on AR content for social media with playtimes of over one minute. Among the agency's most popular products is the Snapchat Lens “A bedroom in Arles,” which allows you to “enter” Van Gogh's famous painting. Another one was a campaign for Singha Beer aimed at Chelsea soccer fans, where users were asked to cheer while the AR Facebook filter painted their faces white and blue – the Chelsea colors. 4) Areyes Studio Areyes creates innovative and trendy Instagram filters, many of which imitate real-world textures. Some look like latex skin, glass, chainmail, and more. One of the studio's hits is Ultra Shine, a filter that creates a mask of shiny gemstones around your face: Areyes also designs filters to promote specific events and brands, such as the Brave! Factory electronic music festival and Don't Take Fake, a festival of urban subculture. 5) FlyAR FlyAR is based in Finland, and many of its AR projects have to do with manufacturing and engineering. For example, it created an augmented model of an office space and superimposed information about the engineering infrastructure over it. For another client, FlyAR designed a marketing flyer with an interactive 3D model of the company office. One of its biggest projects was an AR experience explaining how cardboard packaging for liquids is made: 6) Foundry Six This mixed-reality studio is known for its AR filters for Snapchat and Instagram. You can give yourself yellow hair, make flowers grow out of your head, and even paint your face green: Apart from filters, Foundry Six also makes AR and VR games and apps. For example, it has a card game where you can see little soldiers appear on your cards and fight each other. In another game, called Rider, you can watch a tiny snowboarder ride up and down any surface in your home. The company even designed a fitness app for AR glasses. 7) Avatar Digital Unlike many other AR agencies, which specialize in games and filters, Avatar designs AR and VR experiences for construction, education, real estate, fashion, and other industries. For example, its Live Educare app uses AR 3D models and audio to help children understand the human body and other classroom subjects. Its Life Auto app allows potential car buyers to explore the interior of a car and even book a test drive from right within the app. 8) FairWorlds FairWorlds positions itself as an immersive agency, creating complex AR and VR experiences for brands like Amazon and Dell, as well as for universities and NGOs. For Dell, FairWorlds created a virtual tour of the company's gigantic modular data centers, which can't be shown live to potential customers due to their size and location. Another project, this time for the Environmental Defence Fund, features a cute robot that leads viewers with AR glasses on a quest to find and fix methane leaks: 9) Triangle Factory This Belgium-based agency approaches AR from various angles – both in games and entertainment and in “serious” applications for brands, health care, and engineering. For example, Triangle Factory built an AR basketball game where you can shoot hoops anywhere on the street or even on your own office desk: On the “serious” side, its app Jori allows customers to not only see how new furniture will look in their room but also customize the product: choose the color, cover material, and more. 10) ScullyLabs ScullyLabs designs AR content for different platforms: HoloLens, Android, iOS, and ARKit. Its clients include Macy's Pandora and Nickelodeon. For Nickelodeon, the agency designed special AR tattoos – stickers that kids could put on themselves. When scanned, the tattoos triggered cartoon videos, puzzles, and fun games. Another interesting project was the AR catalog for Bed, Bath & Beyond, where readers could scan over 900 AR anchors in the text to watch videos and unlock promos. Even before the COVID-19 pandemic, the AR market was forecasted to grow at an amazing rate of 46% every year until 2024. The “new normal” of the virus will create additional openings for AR, with people looking for a way to interact with products from the safety of their home. In a couple of years, AR might become a natural part of our life – just like YouTube or Instagram. The 10 startups we've looked at are definitely helping us move in that direction.

10 AR Agencies to Follow in 2020: From Talking Business Cards to Explorable Paintings

The Time Traders by Andre Alice Norton, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . CHAPTER 11 The Time Traders  Chapter 11 It took Ross a while to learn that the dirty-white walls of this tunnel which were almost entirely opaque, with dark objects showing dimly through them here and there, were of solid ice. A black wire was hooked overhead and at regular intervals hung with lights which did nothing to break the sensation of glacial cold about them. Ross shuddered. Every breath he drew stung in his lungs; his bare shoulders and arms and the exposed section of thigh between kilt and boot were numb. He could only move on stiffly, pushed ahead by his guards when he faltered. He guessed that were he to lose his footing here and surrender to the cold, he would forfeit the battle entirely and with it his life. He had no way of measuring the length of the boring through the solid ice, but they were at last fronted by another opening, a ragged one which might have been hacked with an ax. They emerged from it into the wildest scene Ross had ever seen. Of course, he was familiar with ice and snow, but here was a world surrendered completely to the brutal force of winter in a strange, abnormal way. It was a still, dead white-gray world in which nothing moved save the wind which curled the drifts. His guards covered their eyes with the murky lenses they had worn pushed up on their foreheads within the shelter, for above them sunlight dazzled on the ice crest. Ross, his eyes smarting, kept his gaze centered on his feet. He was given no time to look about. A rope was produced, a loop of it flipped in a noose about his throat, and he was towed along like a leashed dog. Before them was a path worn in the snow, not only by the passing of booted feet, but with more deeply scored marks as if heavy objects had been sledded there. Ross slipped and stumbled in the ruts, fearing to fall lest he be dragged. The numbness of his body reached into his head. He was dizzy, the world about him misting over now and again with a haze which arose from the long stretches of unbroken snow fields. Tripping in a rut, he went down upon one knee, his flesh too numbed now to feel the additional cold of the snow, snow so hard that its crust delivered a knife's cut. Unemotionally, he watched a thin line of red trickle in a sluggish drop or two down the blue skin of his leg. The rope jerked him forward, and Ross scrambled awkwardly until one of his captors hooked a fur mitten in his belt and heaved him to his feet once more. The purpose of that trek through the snow was obscure to Ross. In fact, he no longer cared, save that a hard rebel core deep inside him would not let him give up as long as his legs could move and he had a scrap of conscious will left in him. It was more difficult to walk now. He skidded and went down twice more. Then, the last time he slipped, he sledded past the man who led him, sliding down the slope of a glass-slick slope. He lay at the foot, unable to get up. Through the haze and deadening blanket of the cold he knew that he was being pulled about, shaken, generally mishandled; but this time he could not respond. Someone snapped open the rings about his wrists. There was a call, echoing eerily across the ice. The fumbling about his body changed to a tugging and once more he was sent rolling down the slope. But the rope was now gone from his throat, and his arms were free. This time when he brought up hard against an obstruction he was not followed. Ross's conscious mind—that portion of him that was Rossa, the trader—was content to lie there, to yield to the lethargy born of the frigid world about him. But the subconscious Ross Murdock of the Project prodded at him. He had always had a certain cold hatred which could crystalize and become a spur. Once it had been hatred of circumstances and authority; now it became hatred for those who had led him into this wilderness with the purpose, as he knew now, of leaving him to freeze and die. Ross pulled his hands under him. Though there was no feeling in them, they obeyed his will clumsily. He levered himself up and looked around. He lay in a narrow crevicelike cut, partly walled in by earth so frozen as to resemble steel. Crusted over it in long streaks from above were tongues of ice. To remain here was to serve his captors' purpose. Ross inched his way to his feet. This opening, which was intended as his grave, was not so deep as the men had thought it in their hurry to be rid of him. He believed that he could climb out if he could make his body answer to his determination. Somehow Ross made that supreme effort and came again to the rutted path from which they had tumbled him. Even if he could, there was no sense in going along that rutted trail, for it led back to the ice-encased building from which he had been brought. They had thrust him out to die; they would not take him in. But a road so well marked must have some goal, and in hopes that he might find shelter at the other end, Ross turned to the left. The trace continued down the slope. Now the towering walls of ice and snow were broken by rocky teeth as if they had bitten deep upon this land, only to be gnawed in return. Rounding one of those rock fangs, Ross looked at a stretch of level ground. Snow lay here, but the beaten-down trail led straight through it to the rounded side of a huge globe half buried in the ground, a globe of dark material which could only be man-made. Ross was past caution. He must get to warmth and shelter or he was done for, and he knew it. Wavering and weaving, he went on, his attention fixed on the door ahead—a closed oval door. With a sob of exhausted effort, Ross threw himself against it. The barrier gave, letting him fall forward into a queer glimmering radiance of bluish light. The light rousing him because it promised more, he crawled on past another door which was flattened back against the inner wall. It was like making one's way down a tube. Ross paused, pressing his lifeless hands against his bare chest under the edge of his tunic, suddenly realizing that there was warmth here. His breath did not puff out in frosty streamers before him, nor did the air sear his lungs when he ventured to draw in more than shallow gulps. With that realization a measure of animal caution returned to him. To remain where he was, just inside the entrance, was to court disaster. He must find a hiding place before he collapsed, for he sensed he was very near the end of his ability to struggle. Hope had given him a flash of false strength, the impetus to move, and he must make the most of that gift. His path ended at a wide ladder, coiling in slow curves into gloom below and shadows above. He sensed that he was in a building of some size. He was afraid to go down, for even looking in that direction almost finished his sense of balance, so he climbed up. Step by step, Ross made that painful journey, passing levels from which three or four hallways ran out like the radii of a spider's web. He was close to the end of his endurance when he heard a sound, echoed, magnified, from below. It was someone moving. He dragged his body into the fourth level where the light was very faint, hoping to crawl far enough into one of the passages to remain unseen from the stair. But he had gone only part-way down his chosen road when he collapsed, panting, and fell back against the wall. His hands pawed vainly against that sleek surface. He was falling through it! Ross had a second, perhaps two, of stupefied wonder. Lying on a soft surface, he was enfolded by a warmth which eased his bruised and frozen body. There was a sharp prick in his thigh, another in his arm, and the world was a hazy dream until he finally slept in the depths of exhaustion. There were dreams, detailed ones, and Ross stirred uneasily as his sleep thinned to waking. He lay with his eyes closed, fitting together odd bits of—dreams? No, he was certain that they were memories. Rossa of the Beaker traders and Ross Murdock of the project were again fused into one and the same person. How it had happened he did not know, but it was true. Opening his eyes, he noticed a curved ceiling of soft blue which misted at the edges into gray. The restful color acted on his troubled, waking mind like a soothing word. For the first time since he had been struck down in the night his headache was gone. He raised his hand to explore that old hurt near his hairline that had been so tender only yesterday that it could not bear pressure. There remained only a thin, rough line like a long-healed scar, that was all. Ross lifted his head to look about him. His body lay supported in a cradlelike arrangement of metal, almost entirely immersed in a red gelatinous substance with a clean, aromatic odor. Just as he was no longer cold, neither was he hungry. He felt as fit as he ever had in his life. Sitting up in the cradle, he stroked the jelly away from his shoulders and chest. It fell from him cleanly, leaving no trace of grease or dampness on his skin. There were other fixtures in the small cylinderlike chamber besides that odd bed in which he had lain. Two bucket-shaped seats were placed at the narrow fore part of the room and before those seats was a system of controls he could not comprehend. As Ross swung his feet to the floor there was a click from the side which brought him around, ready for trouble. But the noise had been caused by the opening of a door into a small cupboard. Inside the cupboard lay a fat package. Obviously this was an invitation to investigate the offering. The package contained a much folded article of fabric, compressed and sealed in a transparent bag which he fumbled twice before he succeeded in releasing its fastening. Ross shook out a garment of material such as he had never seen before. Its sheen and satin-smooth surface suggested metal, but its stuff was as supple as fine silk. Color rippled across it with every twist and turn he gave to the length—dark blue fading to pale violet, accented with wavering streaks of vivid and startling green. Ross experimented with a row of small, brilliant-green studs which made a transverse line from the right shoulder to the left hip, and they came apart. As he climbed into the suit the stuff modeled to his body in a tight but perfect fit. Across the shoulders were bands of green to match the studs, and the stockinglike tights were soled with a thick substance which formed a cushion for his feet. He pressed the studs together, felt them lock, and then stood smoothing that strange, beautiful fabric, unable to account for either it or his surroundings. His head was clear; he could remember every detail of his flight up to the time he had fallen through the wall. And he was certain that he had passed through not only one, but two, of the Red time posts. Could this be the third? If so, was he still a captive? Why would they leave him to freeze in the open country one moment and then treat him this way later? He could not connect the ice-encased building from which the Reds had taken him with this one. At the sound of another soft noise Ross glanced over his shoulder just in time to see the cradle of jelly, from which he had emerged, close in upon itself until its bulk was a third of its former size. Compact as a box, it folded up against the wall. Ross, his cushioned feet making no sound, advanced to the bucket-chairs. But lowering his body into one of them for a better look at what vaguely resembled the control of a helicopter—like the one in which he had taken the first stage of his fantastic journey across space and time—he did not find it comfortable. He realized that it had not been constructed to accommodate a body shaped precisely like his own. A body like his own.... That jelly bath or bed or whatever it was.... The clothing which adapted so skillfully to his measurements.... Ross leaned forward to study the devices on the control board, confirming his suspicions. He had made the final jump of them all! He was now in some building of that alien race upon whose existence Millaird and Kelgarries had staked the entire project. This was the source, or one of the sources, from which the Reds were getting the knowledge which fitted no modern pattern. A world encased in ice and a building with strange machinery. This thing—a cylinder with a pilot's seat and a set of controls. Was it an alien place? But the jelly bath—and the rest of it.... Had his presence activated that cupboard to supply him with clothing? And what had become of the tunic he was wearing when he entered? Ross got up to search the chamber. The bed-bath was folded against the wall, but there was no sign of his Beaker clothing, his belt, the hide boots. He could not understand his own state of well being, the lack of hunger and thirst. There were two possible explanations for it all. One was that the aliens still lived here and for some reason had come to his aid. The other was that he stood in a place where robot machinery worked, though those who had set it up were no longer there. It was difficult to separate his memory of the half-buried globe he had seen from his sickness of that moment. Yet he knew that he had climbed and crawled through emptiness, neither seeing nor hearing any other life. Now Ross restlessly paced up and down, seeking the door through which he must have come, but there was not even a line to betray such an opening. "I want out," he said aloud, standing in the center of the cramped room, his fists planted on his hips, his eyes still searching for the vanished door. He had tapped, he had pushed, he had tried every possible way to find it. If he could only remember how he had come in! But all he could recall was leaning against a wall which moved inward and allowed him to fall. But where had he fallen? Into that jelly bath? Ross, stung by a sudden idea, glanced at the ceiling. It was low enough so that by standing on tiptoes he could drum his fingers on its surface. Now he moved to the place directly above where the cradle had swung before it had folded itself away. Rapping and poking, his efforts were rewarded at last. The blue curve gave under his assault. He pushed now, rising on his toes, though in that position he could exert little pressure. Then as if some faulty catch had been released, the ceiling swung up so that he lost his footing and would have fallen had he not caught the back of one of the bucket-seats. He jumped and by hooking his hands over the edge of the opening, was able to work his way up and out, to face a small line of light. His fingers worked at that, and he opened a second door, entering a familiar corridor. Holding the door open, Ross looked back, his eyes widening at what he saw. For it was plain now that he had just climbed out of a machine with the unmistakable outline of a snub-nosed rocket. The small flyer—or a jet, or whatever it was—had been fitted into a pocket in the side of the big structure as a ship into a berth, and it must have been set there to shoot from that enclosing chamber as a bullet is shot from a rifle barrel. But why? Ross's imagination jumped from fact to theory. The torpedo craft could be an atomic jet. All right, he had been in bad shape when he fell into it by chance and the bed machine had caught him as if it had been created for just such a duty. What kind of a small plane would be equipped with a restorative apparatus? Only one intended to handle emergencies, to transport badly injured living things who had to leave the building in a hurry. In other words, a lifeboat! But why would a building need a lifeboat? That would be rather standard equipment for a ship. Ross stepped into the corridor and stared about him with open and incredulous wonder. Could this be some form of ship, grounded here, deserted and derelict, and now being plundered by the Reds? The facts fitted! They fitted so well with all he had been able to discover that Ross was sure it was true. But he determined to prove it beyond all doubt. He closed the door leading to the lifeboat berth, but not so securely that he could not open it again. That was too good a hiding place. On his cushioned feet he padded back to the stairway, and he stood there listening. Far below were sounds, a rasp of metal against metal, a low murmur of muted voices. But from above there was nothing, so he would explore above before he ventured into that other danger zone. Ross climbed, passing two more levels, to come out into a vast room with a curving roof which must fill the whole crown of the globe. Here was such a wealth of machines, controls, things he could not understand that he stood bewildered, content for the moment merely to look. There were—he counted slowly—five control boards like those he had seen in the small escape ship. Each of these was faced by two or three of the bucket-seats, only these swung in webbing. He put his hand on one, and it bobbed elastically. The control boards were so complicated that the one in the lifeboat might have been a child's toy in comparison. The air in the ship had been good; in the lifeboat it had held the pleasant odor of the jelly; but here Ross sniffed a faint but persistent hint of corruption, of an old malodor. He left the vantage point by the stairs and paced between the control boards and their empty swinging seats. This was the main control room, of that he was certain. From this point all the vast bulk beneath him had been set in motion, sailed here and there. Had it been on the sea, or through the air? The globe shape suggested an air-borne craft. But a civilization so advanced as this would surely have left some remains. Ross was willing to believe that he could be much farther back in time than 2000 b.c., but he was still sure that traces of those who could build a thing like this would have existed in the twentieth century a.d. Maybe that was how the Reds had found this. Something they had turned up within their country—say, in Siberia, or some of the forgotten corners of Asia—had been a clue. Having had little schooling other than the intensive cramming at the base and his own informal education, the idea of the race who had created this ship overawed Ross more than he would admit. If the project could find this, turn loose on it the guys who knew about such things.... But that was just what they were striving for, and he was the only project man to have found the prize. Somehow, someway, he had to get back—out of this half-buried ship and its icebound world—back to where he could find his own people. Perhaps the job was impossible, but he had to try. His survival was considered impossible by the men who had thrown him into the crevice, but here he was. Thanks to the men who had built this ship, he was alive and well. Ross sat down in one of the uncomfortable seats to think and thus avoided immediate disaster, for he was hidden from the stairs on which sounded the tap of boots. A climber, maybe two, were on their way up, and there was no other exit from the control cabin. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Andre Alice Norton (2006). The Time Traders. Urbana, Illinois: Project Gutenberg. Retrieved October 2022 https://www.gutenberg.org/cache/epub/19145/pg19145-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html.

BED BATH & BEYOND

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BED BATH & BEYOND

bedbathandbeyond.com

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Since 1971

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