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Google Adds Custom Bidding and Outcome-Based Buying Options for Display & Video 360 Campaigns

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google adds custom bidding and outcome based buying options for display video 360 campaigns

Google has added two new ad bidding options for Display and Video 360 campaigns, giving marketers more control over how their ad budget is allocated through its programmatic process.

Google’s Display campaigns enable marketers to place ads on a range of websites across Google’s network,  while Video 360 campaigns are specific to video across the same.

First off, Google’s adding a new Custom Bidding option which will enable advertisers to set the parameters for their campaign budget allocation.

As explained by Google:

“Here’s how it works: first, you identify a key performance indicator (KPI), such as revenue or brand lift, that you want to optimize. Next, you define the proxy signals that help predict success with your KPI. For example, you might select transaction value as a proxy for revenue or creative dimension as a proxy for brand lift – you can choose as a signal anything that is measurable as a Floodlight activity or a goal in Google Analytics 360.”

Floodlight activity uses HTML code to track conversions, while Analytics 360 goals can incorporate a range of signals based on your website data.

Google Analytics 360 goals

Based on these parameters, you can build new KPIs for your campaigns, which Google’s bidding system will then optimize for.

“You build a script that uses these signals to assign scores to ad impressions in order to define how much each impression is worth to you, based on its expected ability to drive your chosen KPI. Once the campaign starts, Display & Video 360 will use the scoring model built on your script to predict the value of each impression and adjust each bid accordingly.”

It’s a fairly technical addition, for more advanced marketers, but it provides another level of control over the specifics of the automated budgeting process. Which, if you get it right, could better align with your specific campaign objectives.

But it might also be risky – Google’s automated systems have been built to optimize for performance already, and while having more control is good, it could also lead to you reducing effectiveness.

Google’s also adding a new outcome-based buying option, which will enable advertisers to only pay for the results that support their defined goals.

Google outcome-based buying

“Outcome-based buying currently supports performance campaigns by allowing marketers to pay per click for campaigns that use either target cost per acquisition (CPA) or maximize conversions strategies. In the next few months we’ll introduce pay for viewable impressions as measured by Active View both for your display and video campaigns, which will reduce budget waste and increase the impact of your branding campaigns too.”

Essentially, these are advanced options, though depending on how you use Google’s ad tools, they could be relevant to your approach.

Custom Bidding will be made available to all Display & Video 360 accounts in the next few weeks, while support for including Analytics 360 goals as Custom Bidding signals will launch in the next few months.

Socialmediatoday.com

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AI

Exploring the Evolution of Language Translation: A Comparative Analysis of AI Chatbots and Google Translate

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A Comparative Analysis of AI Chatbots and Google Translate

According to an article on PCMag, while Google Translate makes translating sentences into over 100 languages easy, regular users acknowledge that there’s still room for improvement.

In theory, large language models (LLMs) such as ChatGPT are expected to bring about a new era in language translation. These models consume vast amounts of text-based training data and real-time feedback from users worldwide, enabling them to quickly learn to generate coherent, human-like sentences in a wide range of languages.

However, despite the anticipation that ChatGPT would revolutionize translation, previous experiences have shown that such expectations are often inaccurate, posing challenges for translation accuracy. To put these claims to the test, PCMag conducted a blind test, asking fluent speakers of eight non-English languages to evaluate the translation results from various AI services.

The test compared ChatGPT (both the free and paid versions) to Google Translate, as well as to other competing chatbots such as Microsoft Copilot and Google Gemini. The evaluation involved comparing the translation quality for two test paragraphs across different languages, including Polish, French, Korean, Spanish, Arabic, Tagalog, and Amharic.

In the first test conducted in June 2023, participants consistently favored AI chatbots over Google Translate. ChatGPT, Google Bard (now Gemini), and Microsoft Bing outperformed Google Translate, with ChatGPT receiving the highest praise. ChatGPT demonstrated superior performance in converting colloquialisms, while Google Translate often provided literal translations that lacked cultural nuance.

For instance, ChatGPT accurately translated colloquial expressions like “blow off steam,” whereas Google Translate produced more literal translations that failed to resonate across cultures. Participants appreciated ChatGPT’s ability to maintain consistent levels of formality and its consideration of gender options in translations.

The success of AI chatbots like ChatGPT can be attributed to reinforcement learning with human feedback (RLHF), which allows these models to learn from human preferences and produce culturally appropriate translations, particularly for non-native speakers. However, it’s essential to note that while AI chatbots outperformed Google Translate, they still had limitations and occasional inaccuracies.

In a subsequent test, PCMag evaluated different versions of ChatGPT, including the free and paid versions, as well as language-specific AI agents from OpenAI’s GPTStore. The paid version of ChatGPT, known as ChatGPT Plus, consistently delivered the best translations across various languages. However, Google Translate also showed improvement, performing surprisingly well compared to previous tests.

Overall, while ChatGPT Plus emerged as the preferred choice for translation, Google Translate demonstrated notable improvement, challenging the notion that AI chatbots are always superior to traditional translation tools.


Source: https://www.pcmag.com/articles/google-translate-vs-chatgpt-which-is-the-best-language-translator

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Google Implements Stricter Guidelines for Mass Email Senders to Gmail Users

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Beginning in April, Gmail senders bombarding users with unwanted mass emails will encounter a surge in message rejections unless they comply with the freshly minted Gmail email sender protocols, Google cautions.

Fresh Guidelines for Dispatching Mass Emails to Gmail Inboxes In an elucidative piece featured on Forbes, it was highlighted that novel regulations are being ushered in to shield Gmail users from the deluge of unsolicited mass emails. Initially, there were reports surfacing about certain marketers receiving error notifications pertaining to messages dispatched to Gmail accounts. Nonetheless, a Google representative clarified that these specific errors, denoted as 550-5.7.56, weren’t novel but rather stemmed from existing authentication prerequisites.

Moreover, Google has verified that commencing from April, they will initiate “the rejection of a portion of non-compliant email traffic, progressively escalating the rejection rate over time.” Google elaborates that, for instance, if 75% of the traffic adheres to the new email sender authentication criteria, then a portion of the remaining non-conforming 25% will face rejection. The exact proportion remains undisclosed. Google does assert that the implementation of the new regulations will be executed in a “step-by-step fashion.”

This cautious and methodical strategy seems to have already kicked off, with transient errors affecting a “fraction of their non-compliant email traffic” coming into play this month. Additionally, Google stipulates that bulk senders will be granted until June 1 to integrate “one-click unsubscribe” in all commercial or promotional correspondence.

Exclusively Personal Gmail Accounts Subject to Rejection These alterations exclusively affect bulk emails dispatched to personal Gmail accounts. Entities sending out mass emails, specifically those transmitting a minimum of 5,000 messages daily to Gmail accounts, will be mandated to authenticate outgoing emails and “refrain from dispatching unsolicited emails.” The 5,000 message threshold is tabulated based on emails transmitted from the same principal domain, irrespective of the employment of subdomains. Once the threshold is met, the domain is categorized as a permanent bulk sender.

These guidelines do not extend to communications directed at Google Workspace accounts, although all senders, including those utilizing Google Workspace, are required to adhere to the updated criteria.

Augmented Security and Enhanced Oversight for Gmail Users A Google spokesperson emphasized that these requisites are being rolled out to “fortify sender-side security and augment user control over inbox contents even further.” For the recipient, this translates to heightened trust in the authenticity of the email sender, thus mitigating the risk of falling prey to phishing attempts, a tactic frequently exploited by malevolent entities capitalizing on authentication vulnerabilities. “If anything,” the spokesperson concludes, “meeting these stipulations should facilitate senders in reaching their intended recipients more efficiently, with reduced risks of spoofing and hijacking by malicious actors.”

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GOOGLE

Google’s Next-Gen AI Chatbot, Gemini, Faces Delays: What to Expect When It Finally Launches

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Google AI Chatbot Gemini

In an unexpected turn of events, Google has chosen to postpone the much-anticipated debut of its revolutionary generative AI model, Gemini. Initially poised to make waves this week, the unveiling has now been rescheduled for early next year, specifically in January.

Gemini is set to redefine the landscape of conversational AI, representing Google’s most potent endeavor in this domain to date. Positioned as a multimodal AI chatbot, Gemini boasts the capability to process diverse data types. This includes a unique proficiency in comprehending and generating text, images, and various content formats, even going so far as to create an entire website based on a combination of sketches and written descriptions.

Originally, Google had planned an elaborate series of launch events spanning California, New York, and Washington. Regrettably, these events have been canceled due to concerns about Gemini’s responsiveness to non-English prompts. According to anonymous sources cited by The Information, Google’s Chief Executive, Sundar Pichai, personally decided to postpone the launch, acknowledging the importance of global support as a key feature of Gemini’s capabilities.

Gemini is expected to surpass the renowned ChatGPT, powered by OpenAI’s GPT-4 model, and preliminary private tests have shown promising results. Fueled by significantly enhanced computing power, Gemini has outperformed GPT-4, particularly in FLOPS (Floating Point Operations Per Second), owing to its access to a multitude of high-end AI accelerators through the Google Cloud platform.

SemiAnalysis, a research firm affiliated with Substack Inc., expressed in an August blog post that Gemini appears poised to “blow OpenAI’s model out of the water.” The extensive compute power at Google’s disposal has evidently contributed to Gemini’s superior performance.

Google’s Vice President and Manager of Bard and Google Assistant, Sissie Hsiao, offered insights into Gemini’s capabilities, citing examples like generating novel images in response to specific requests, such as illustrating the steps to ice a three-layer cake.

While Google’s current generative AI offering, Bard, has showcased noteworthy accomplishments, it has struggled to achieve the same level of consumer awareness as ChatGPT. Gemini, with its unparalleled capabilities, is expected to be a game-changer, demonstrating impressive multimodal functionalities never seen before.

During the initial announcement at Google’s I/O developer conference in May, the company emphasized Gemini’s multimodal prowess and its developer-friendly nature. An application programming interface (API) is under development, allowing developers to seamlessly integrate Gemini into third-party applications.

As the world awaits the delayed unveiling of Gemini, the stakes are high, with Google aiming to revolutionize the AI landscape and solidify its position as a leader in generative artificial intelligence. The postponed launch only adds to the anticipation surrounding Gemini’s eventual debut in the coming year.

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