AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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1,707 papers
It is found that what perceived as biggest challenges by software startups do vary across different life cycle stages, even though its significance decreases when the learning focuses of the startups move from problem to solution and their products mature.
Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.
A case study of a large software company was conducted to examine how a new product was developed through the internal startup effort and struggled to achieve the desired outcomes set by the management, and the conceptual framework was developed into a Lean startup-enabled new product development model for large softwa...
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It is found that roles of MVPs in startups were not fully aware by entrepreneurs, and entrepreneurs should consider a systematic approach to fully explore the value of MVP, as a multiple facet product (MFP).
This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.
The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.
The initial findings show that different software startups make different types of pivots related to business and technology during their product development life cycle, which are triggered by various factors including negative customer feedback.
This paper reports a study where realism was combined with control over certain context and process factors to identify the most important relationships among process, context and outcome.
It is proposed that early contract-based activities could be transformed into a long-term partnership by adopting a startup boundary spanner's role, establishing an inter-personal relationship and maintaining a mutual commitment.
The results indicate that software developers are a slightly happy population, but the need for limiting the unhappiness of developers remains, and 219 factors representing causes of unhappiness while developing software are identified.
The behaviour theory of entrepreneurial firms is applied to understand the root-cause of some software startup challenges and implies that effectual entrepreneurial processes might require a more suitable product development approach than the current state-of-practice.
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
Able to defeat top-ranked human players and more efficient than other models, the new system could help decision-makers in military maneuvers or business negotiations.
A Blog post by H company on Hugging Face
The PKG Center for Social Impact expands Code.Tulsa experiential learning program.
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
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