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RFK Jr. dropping out of the 2024 race may assist Trump

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Arguably the weirdest candidate of the 2024 election is successfully ending his presidential marketing campaign.

Following a controversy-filled marketing campaign that included revelations {that a} worm had eaten a part of his mind and that he was answerable for the bear carcass that mysteriously appeared in Central Park in 2014, Robert F. Kennedy Jr. introduced that he’s withdrawing his presidential bid together with his working mate Nicole Shanahan in 10 battleground states the place his presence may make him a spoiler for former President Donald Trump or Vice President Kamala Harris. He stated his title will stay on the poll elsewhere.

He additionally endorsed Trump, reportedly hopeful that he may safe the place of Trump’s well being secretary if he wins.

Kennedy was as soon as an environmental lawyer with a storied final title identified for his work cleansing up the Hudson River. Lately, nonetheless, he has turn into identified for spreading conspiracy theories about medication, together with vaccines and anti-depressants. He used the recognition he gained as an anti-vaxxer in the course of the pandemic to briefly problem President Joe Biden within the Democratic main earlier than saying an unbiased bid for president in October 2023.

He had been seen as a possible spoiler for each candidates, given his connection to the Democratic Kennedy dynasty in addition to his embrace of the anti-establishment and anti-vaccine views held by sure segments of the GOP. He was polling round 10 % nationally for the higher a part of 2024, and even increased in some swing state polls.

However he struggled to get on the poll in lots of states, although his marketing campaign maintains that he has secured sufficient signatures to take action in all however Kentucky, Mississippi, Rhode Island, and Wyoming. After Harris grew to become the Democratic nominee, he appeared to carry much less sway amongst voters who had been turned off by Biden. His ballot numbers consequently cratered to below 5 %.

Regardless of Kennedy’s flagging nationwide numbers, polling suggests his exit from the race may nonetheless assist Trump, with whom he’s turn into decidedly extra cozy in current months. Trump wouldn’t need to win a variety of Kennedy’s potential voters to make a distinction in key swing states; if the race is as shut because it was in 2020, Trump gaining even a fraction of a % from Kennedy may make the distinction.

Kennedy’s exit might assist Trump the place it issues probably the most

Trump most likely has probably the most to realize from Kennedy dropping out. Kennedy has more and more endeared himself to Republican voters whereas struggling to get the identical help amongst Democrats and independents. And polls carried out in current months, together with since Biden dropped out of the race, recommend that Trump would choose up extra of Kennedy’s supporters. Any margin would possible be small — however probably vital.

Republicans are likely to see Kennedy extra favorably than Democrats, and people with favorable views towards him are likely to have extra favorable opinions of Trump than of Harris, in accordance with a July AP-NORC ballot carried out earlier than Biden dropped out.

A number of nationwide polls carried out since Harris grew to become the presumptive nominee have additionally examined a race between Harris, Trump, and Kennedy, in addition to a two-way race between Harris and Trump. Trump tends to get a much bigger bump than Harris when Kennedy is excluded.

In an August Reuters/Ipsos ballot of registered voters, as an example, Harris acquired 42 % help, Trump 37 %, and Kennedy 4 %, whereas 15 % supported one other candidate, weren’t positive who they’d help, or weren’t positive if they’d vote in any respect. However when voters had been pushed to pick both Trump or Harris, 49 % backed Harris and 47 % Trump — a ten share level enhance for Trump.

Trump had the same edge with Kennedy voters in a July Harvard CAPS/Harris Ballot. In a three-way contest, Harris earned 44 % help, Trump 47 %, and Kennedy 10 %. In a head-to-head ballot, Harris earned 48 % and Trump 52 %.

It might look like the benefit Trump positive factors when Kennedy is out of the image is comparatively small. However Biden received in 2020 by exceedingly slim margins in six key battleground states; in Arizona, it was by lower than 11,000 votes. On the margin, Kennedy’s supporters may make a distinction, relying on the place they’re distributed.

In Arizona, for instance, Kennedy is polling at about 6 %, in accordance with The Hill’s polling common. In fact, he may not have truly received that enormous a vote share if he had determined to remain within the race there; third-party candidates are likely to ballot a lot better than they really carry out on Election Day, when their supporters are confronted with the fact that their most popular candidate received’t win. However that vote share would have been greater than sufficient to have swung the 2020 ends in the opposite path.

The identical is true in different swing states, the place polling suggests a really tight race. An early August New York Instances/Siena survey of registered voters in Michigan, Pennsylvania, and Wisconsin discovered Harris main Trump 46 % to 43 % when respondents got all third-party candidates to select from. When requested to choose between simply Harris and Trump, the hole tightened to 48 and 46 %, respectively. These states are more likely to be key, given their excessive electoral school vote rely — and in most eventualities, Harris would want all three to win.

Harris’s entry into the race possible limits the affect of Kennedy’s exit

Whereas Kennedy’s supporters should have the ability to make an essential affect on the margins, their energy to pull the Democratic nominee’s polling down appears to have diminished considerably.

Earlier than Harris grew to become the nominee, there was a a lot bigger than common variety of disaffected voters who didn’t like both Biden or Trump and simply needed somebody — anybody — as a substitute. A theoretical no-name candidate as a substitute for Biden and Trump obtained about 10 % in Ipsos polling carried out earlier this 12 months.

Kennedy offered another for some time. However when Harris stepped up, that undermined his attraction — a minimum of amongst Democrats.

“There have been some wavering Democratic voters who simply thought Biden was too previous, or they didn’t like him, and Harris is only a extra interesting candidate for these sorts of individuals,” stated Kyle Kondik, managing editor of Sabato’s Crystal Ball on the College of Virginia Heart for Politics.

Kondik stated it’s doable that Biden might have ended up successful again these voters anyway if he had stayed within the race and had a typical post-Democratic Nationwide Conference bump.

However at this level, Kondik stated, he wouldn’t be stunned if the third-party vote share within the election finally ends up being about 2 % of the voters, because it was in 2012 and 2020. Earlier than Harris grew to become the nominee, political analysts had been projecting that it could be nearer to the practically 6 % share third events obtained in 2016, which some analysts argued doomed Democratic nominee Hillary Clinton’s candidacy.

“For all of the speak about third events on this election, a mixture of probably the most distinguished third-party candidate dropping out, along with the elevated favorability of the 2 main get together nominees, implies that there’s simply going to be much less of a marketplace for third-party candidates,” he stated.

Kennedy may make extra of an affect as a surrogate for Trump. He may assist the previous president with sure demographics, corresponding to younger males who take heed to distinguished personalities corresponding to Joe Rogan, who has praised Kennedy.

However the Trump marketing campaign may additionally be cautious of attaching itself too intently to Kennedy’s model: If the mind worm and the bear incident weren’t sufficient, he has been disavowed by members of his personal well-known household and now peddles conspiracy theories not simply in regards to the Covid-19 vaccine, however his father’s killer, 5G cellphone transmission, fraud within the 2004 election, and extra.

“The Democratic chorus towards Trump and [his running mate JD] Vance is that they’re ‘bizarre,’” Kondik stated. “Kennedy doesn’t make them much less bizarre.”

Replace, August 23, 4 pm: This story was initially printed on August 22 and has been up to date to incorporate Kennedy’s announcement about dropping out in 10 states.

HBCU college students chart their profession paths in America’s Music Metropolis

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How we fought unhealthy apps and unhealthy actors in 2023


A protected and trusted Google Play expertise is our prime precedence. We leverage our SAFE (see under) ideas to supply the framework to create that have for each customers and builders. Here is what these ideas imply in observe:

  • (S)afeguard our Customers. Assist them uncover high quality apps that they’ll belief.
  • (A)dvocate for Developer Safety. Construct platform safeguards to allow builders to give attention to development.
  • (F)oster Accountable Innovation. Thoughtfully unlock worth for all with out compromising on person security.
  • (E)volve Platform Defenses. Keep forward of rising threats by evolving our insurance policies, instruments and know-how.

With these ideas in thoughts, we’ve made latest enhancements and launched new measures to proceed to maintain Google Play’s customers protected, even because the menace panorama continues to evolve. In 2023, we prevented 2.28 million policy-violating apps from being revealed on Google Play1 partly due to our funding in new and improved security measures, coverage updates, and superior machine studying and app evaluate processes. Now we have additionally strengthened our developer onboarding and evaluate processes, requiring extra id data when builders first set up their Play accounts. Along with investments in our evaluate tooling and processes, we recognized unhealthy actors and fraud rings extra successfully and banned 333K unhealthy accounts from Play for violations like confirmed malware and repeated extreme coverage violations.

Moreover, nearly 200K app submissions have been rejected or remediated to make sure correct use of delicate permissions reminiscent of background location or SMS entry. To assist safeguard person privateness at scale, we partnered with SDK suppliers to restrict delicate information entry and sharing, enhancing the privateness posture for over 31 SDKs impacting 790K+ apps. We additionally considerably expanded the Google Play SDK Index, which now covers the SDKs utilized in nearly 6 million apps throughout the Android ecosystem. This priceless useful resource helps builders make higher SDK decisions, boosts app high quality and minimizes integration dangers.

Defending the Android Ecosystem

Constructing on our success with the App Protection Alliance (ADA), we partnered with Microsoft and Meta as steering committee members within the newly restructured ADA below the Joint Improvement Basis, a part of the Linux Basis household. The Alliance will help industry-wide adoption of app safety finest practices and tips, in addition to countermeasures towards rising safety dangers.

Moreover, we introduced new Play Retailer transparency labeling to spotlight VPN apps which have accomplished an unbiased safety evaluate by App Protection Alliance’s Cellular App Safety Evaluation (MASA). When a person searches for VPN apps, they may now see a banner on the prime of Google Play that educates them in regards to the “Impartial safety evaluate” badge within the Information security part. This helps customers see at-a-glance {that a} developer has prioritized safety and privateness finest practices and is dedicated to person security.

To raised defend our clients who set up apps outdoors of the Play Retailer, we made Google Play Shield’s safety capabilities much more highly effective with real-time scanning on the code-level to fight novel malicious apps. Our safety protections and machine studying algorithms study from every app submitted to Google for evaluate and we take a look at hundreds of alerts and evaluate app conduct. This new functionality has already detected over 5 million new, malicious off-Play apps, which helps defend Android customers worldwide.

Extra Stringent Developer Necessities and Tips

Final 12 months we up to date Play insurance policies round Generative AI apps, disruptive notifications, and expanded privateness protections. We are also elevating the bar for brand new private developer accounts by requiring new testing necessities earlier than builders could make their app accessible on Google Play. By testing their apps, getting suggestions and guaranteeing all the pieces is prepared earlier than they launch, builders are capable of carry extra prime quality content material to Play customers. As a way to enhance belief and transparency, we’ve launched expanded developer verification necessities, together with D-U-N-S numbers for organizations and a brand new “Concerning the developer” part.

To provide customers extra management over their private information, apps that allow account creation now want to supply an choice to provoke account and information deletion from inside the app and on-line. This net requirement is particularly vital so {that a} person can request account and information deletion with out having to reinstall an app. To simplify the person expertise, we’ve got additionally included this as a function inside the Information security part of the Play Retailer.

With every iteration of the Android working system (together with its strong set of APIs), a myriad of enhancements are launched, aiming to raise the person expertise, bolster safety protocols, and optimize the general efficiency of the Android platform. To additional safeguard our clients, roughly 1.5 million functions that don’t goal the newest APIs are now not accessible within the Play Retailer to new customers who’ve up to date their units to the newest Android model.

Wanting Forward

Defending customers and builders on Google Play is paramount and ever-evolving. We’re launching new safety initiatives in 2024, together with eradicating apps from Play that aren’t clear about their privateness practices.

We additionally not too long ago filed a lawsuit in federal court docket towards two fraudsters who made a number of misrepresentations to add fraudulent funding and crypto trade apps on Play to rip-off customers. This lawsuit is a vital step in holding these unhealthy actors accountable and sending a transparent message that we are going to aggressively pursue those that search to reap the benefits of our customers.

We’re always engaged on new methods to guard your expertise on Google Play and throughout the whole Android ecosystem, and we stay up for sharing extra.

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Introducing Cloudera’s AI Assistants – Cloudera Weblog

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Within the final couple of years, AI has launched itself to the forefront of expertise initiatives throughout industries. In truth, Gartner predicts the AI software program market will develop from $124 billion in 2022 to $297 billion in 2027. As an information platform firm, Cloudera has two very clear priorities. First, we have to assist prospects get AI fashions primarily based on trusted knowledge into manufacturing quicker than ever. And second, we have to construct AI capabilities into Cloudera to present extra folks entry to data-driven insights for his or her on a regular basis roles.

At our current Cloudera Now digital occasion, we introduced three new capabilities that assist each of our AI priorities: An AI-driven SQL assistant, a Enterprise Intelligence (BI) chatbot that converses together with your knowledge, and an ML copilot that accelerates machine studying improvement. Let’s take a deeper dive into how these capabilities speed up your AI initiatives and assist knowledge democratization.

SQL AI Assistant: Your New Finest Buddy

Writing advanced SQL queries could be a actual problem. From discovering the fitting tables and columns to coping with joins, unions, and subselects, then optimizing for readability and efficiency, and doing all of that whereas taking into consideration the distinctive SQL dialect of the engine, it’s sufficient to make even probably the most seasoned SQL developer’s head spin.  And on the finish of the day, not everybody who wants knowledge to achieve success of their day-to-day work is an SQL professional.

Think about, as a substitute, having a site professional and a SQL guru at all times by your aspect. That’s precisely what Cloudera’s SQL AI assistant is. Customers merely describe what they want in plain language, and the assistant will discover the related knowledge, write the question, optimize it, and even clarify it again in easy-to-understand phrases. 

 

 

Underneath the hood, the assistant makes use of superior methods like immediate engineering and retrieval augmented technology (RAG) to actually perceive your database. It really works with many massive language fashions (LLMs), whether or not they’re public or non-public, and it effortlessly scales to deal with 1000’s of tables and customers concurrently. So whether or not you’re beneath strain to reply vital enterprise questions or simply uninterested in wrestling with SQL syntax, the AI assistant has your again, enabling you to give attention to what actually issues – getting insights out of your knowledge.

AI Chatbot in Cloudera Knowledge Visualization: Your Knowledge’s New Finest Buddy

BI dashboards are undeniably helpful, however they usually solely inform a part of the story. To realize significant and actionable insights, knowledge customers want to have interaction in a dialog with their knowledge, and ask questions past merely the “what” {that a} dashboard usually exhibits. That’s the place the AI Chatbot in Cloudera Knowledge Visualization comes into play.

 

The chatbot resides straight inside your dashboard, able to reply any query you pose. And once we say “any query,” we imply it. Why are gross sales down within the Northeast? Will this pattern proceed? What actions ought to we take? The chatbot leverages the context of the information behind the dashboard to ship deeper, extra actionable insights to the consumer. 

A written reply is an effective way to begin understanding your knowledge, however let’s not overlook the facility of the visuals in our dashboards and experiences.  The chatbot eliminates the burden of clicking by dropdowns and filters to search out solutions. Merely ask what you need to know, in plain language, and the chatbot will intelligently match it to the related knowledge and visuals. It’s like having a devoted material professional proper there with you, able to dive deep into the insights that matter most to your enterprise.

Cloudera Copilot for Cloudera Machine Studying: Your Mannequin’s New Finest Buddy

Constructing machine studying fashions is not any simple feat. From knowledge wrangling to coding, mannequin tuning to deployment, it’s a posh and time-consuming course of. In truth, many fashions by no means make it into manufacturing in any respect. However what for those who had a copilot to assist navigate all the challenges associated to deploying fashions in manufacturing?

 

Cloudera’s ML copilots, powered by pre-trained LLMs, are like having machine studying specialists on name 24/7. They’ll write and debug Python code, counsel enhancements, and even generate whole functions from scratch. With seamless integration to over 130 Hugging Face fashions and datasets, you have got a wealth of sources at your disposal.

Whether or not you’re an information scientist trying to streamline your workflow or a enterprise consumer desperate to get an AI utility up and operating rapidly, the ML copilots assist the end-to-end improvement course of and get fashions into manufacturing quick.

Elevate Your Knowledge with AI Assistants

By embedding AI assistants for SQL, BI, and ML straight into the platform, Cloudera is simplifying and enhancing the information expertise for each single consumer. SQL builders shall be extra environment friendly and productive than ever. Enterprise analysts shall be empowered to have significant, actionable conversations with knowledge, uncovering the “why” behind the “what.” Moreover, knowledge scientists shall be empowered to deliver new AI functions to manufacturing quicker and with higher confidence.

For extra data on these options and our AI capabilities, go to our Enterprise AI web page. If you’re prepared, you possibly can request a demo on the backside of the web page to see how these capabilities can work within the context of your enterprise.  

Occasion Interception


By the point adjustments have made their method to the legacy database, then you can argue that it’s too late for
occasion interception.
That mentioned, “Pre-commit” triggers can be utilized to intercept a database write occasion and take completely different actions.
For instance a row could possibly be inserted right into a separate Occasions desk to be learn/processed by a brand new part –
while continuing with the write as earlier than (or aborting it).
Observe that important care needs to be taken in the event you change the present write behaviour as chances are you’ll be breaking
an important implicit contract.

Case Research: Incremental area extraction

Considered one of our groups was working for a consumer whose legacy system had stability points and had turn out to be tough to keep up and gradual to replace.

The organisation was seeking to treatment this, and it had been determined that essentially the most acceptable approach ahead for them was to displace the legacy system with capabilities realised by a Service Primarily based Structure.

The technique that the workforce adopted was to make use of the Strangler Fig sample and extract domains, one after the other, till there was little to not one of the unique software left.
Different concerns that had been in play included:

  • The necessity to proceed to make use of the legacy system with out interruption
  • The necessity to proceed to permit upkeep and enhancement to the legacy system (although minimising adjustments to domains being extracted was allowed)
  • Modifications to the legacy software had been to be minimised – there was an acute scarcity of retained data of the legacy system

Legacy state

The diagram beneath exhibits the structure of the legacy
structure. The monolithic system’s
structure was primarily Presentation-Area-Knowledge Layers.

Occasion Interception

Stage 1 – Darkish launch service(s) for a single area

Firstly the workforce created a set of companies for a single enterprise area together with the potential for the information
uncovered by these companies to remain in sync with the legacy system.

The companies used Darkish Launching – i.e. not utilized by any shoppers, as an alternative the companies allowed the workforce to
validate that knowledge migration and synchronisation achieved 100% parity with the legacy datastore.
The place there have been points with reconciliation checks, the workforce might motive about, and repair them guaranteeing
consistency was achieved – with out enterprise affect.

The migration of historic knowledge was achieved by way of a “single shot” knowledge migration course of. While not strictly Occasion Interception, the continuing
synchronisation was achieved utilizing a Change Knowledge Seize (CDC) course of.

Stage 2 – Intercept all reads and redirect to the brand new service(s)

For stage 2 the workforce up to date the legacy Persistence Layer to intercept and redirect all of the learn operations (for this area) to
retrieve the information from the brand new area service(s). Write operations nonetheless utilised the legacy knowledge retailer. That is
and instance of Department by Abstraction – the interface of the Persistence Layer stays unchanged and a brand new underlying implementation
put in place.

Stage 3 – Intercept all writes and redirect to the brand new service(s)

At stage 3 various adjustments occurred. Write operations (for the area) had been intercepted and redirected to create/replace/take away
knowledge throughout the new area service(s).

This variation made the brand new area service the System of Report for this knowledge, because the legacy knowledge retailer was now not up to date.
Any downstream utilization of that knowledge, equivalent to reviews, additionally needed to be migrated to turn out to be a part of or use the brand new
area service.

Stage 4 – Migrate area enterprise guidelines / logic to the brand new service(s)

At stage 4 enterprise logic was migrated into the brand new area companies (remodeling them from anemic “knowledge companies”
into true enterprise companies). The entrance finish remained unchanged, and was now utilizing a legacy facade which
redirected implementation to the brand new area service(s).